---
_id: '10853'
abstract:
- lang: eng
text: Dynamic Connectivity is a fundamental algorithmic graph problem, motivated
by a wide range of applications to social and communication networks and used
as a building block in various other algorithms, such as the bi-connectivity and
the dynamic minimal spanning tree problems. In brief, we wish to maintain the
connected components of the graph under dynamic edge insertions and deletions.
In the sequential case, the problem has been well-studied from both theoretical
and practical perspectives. However, much less is known about efficient concurrent
solutions to this problem. This is the gap we address in this paper. We start
from one of the classic data structures used to solve this problem, the Euler
Tour Tree. Our first contribution is a non-blocking single-writer implementation
of it. We leverage this data structure to obtain the first truly concurrent generalization
of dynamic connectivity, which preserves the time complexity of its sequential
counterpart, but is also scalable in practice. To achieve this, we rely on three
main techniques. The first is to ensure that connectivity queries, which usually
dominate real-world workloads, are non-blocking. The second non-trivial technique
expands the above idea by making all queries that do not change the connectivity
structure non-blocking. The third ingredient is applying fine-grained locking
for updating the connected components, which allows operations on disjoint components
to occur in parallel. We evaluate the resulting algorithm on various workloads,
executing on both real and synthetic graphs. The results show the efficiency of
each of the proposed optimizations; the most efficient variant improves the performance
of a coarse-grained based implementation on realistic scenarios up to 6x on average
and up to 30x when connectivity queries dominate.
article_processing_charge: No
arxiv: 1
author:
- first_name: Alexander
full_name: Fedorov, Alexander
last_name: Fedorov
- first_name: Nikita
full_name: Koval, Nikita
last_name: Koval
- first_name: Dan-Adrian
full_name: Alistarh, Dan-Adrian
id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
last_name: Alistarh
orcid: 0000-0003-3650-940X
citation:
ama: 'Fedorov A, Koval N, Alistarh D-A. A scalable concurrent algorithm for dynamic
connectivity. In: Proceedings of the 33rd ACM Symposium on Parallelism in Algorithms
and Architectures. Association for Computing Machinery; 2021:208-220. doi:10.1145/3409964.3461810'
apa: 'Fedorov, A., Koval, N., & Alistarh, D.-A. (2021). A scalable concurrent
algorithm for dynamic connectivity. In Proceedings of the 33rd ACM Symposium
on Parallelism in Algorithms and Architectures (pp. 208–220). Virtual, Online:
Association for Computing Machinery. https://doi.org/10.1145/3409964.3461810'
chicago: Fedorov, Alexander, Nikita Koval, and Dan-Adrian Alistarh. “A Scalable
Concurrent Algorithm for Dynamic Connectivity.” In Proceedings of the 33rd
ACM Symposium on Parallelism in Algorithms and Architectures, 208–20. Association
for Computing Machinery, 2021. https://doi.org/10.1145/3409964.3461810.
ieee: A. Fedorov, N. Koval, and D.-A. Alistarh, “A scalable concurrent algorithm
for dynamic connectivity,” in Proceedings of the 33rd ACM Symposium on Parallelism
in Algorithms and Architectures, Virtual, Online, 2021, pp. 208–220.
ista: 'Fedorov A, Koval N, Alistarh D-A. 2021. A scalable concurrent algorithm for
dynamic connectivity. Proceedings of the 33rd ACM Symposium on Parallelism in
Algorithms and Architectures. SPAA: Symposium on Parallelism in Algorithms and
Architectures, 208–220.'
mla: Fedorov, Alexander, et al. “A Scalable Concurrent Algorithm for Dynamic Connectivity.”
Proceedings of the 33rd ACM Symposium on Parallelism in Algorithms and Architectures,
Association for Computing Machinery, 2021, pp. 208–20, doi:10.1145/3409964.3461810.
short: A. Fedorov, N. Koval, D.-A. Alistarh, in:, Proceedings of the 33rd ACM Symposium
on Parallelism in Algorithms and Architectures, Association for Computing Machinery,
2021, pp. 208–220.
conference:
end_date: 2021-07-08
location: Virtual, Online
name: 'SPAA: Symposium on Parallelism in Algorithms and Architectures'
start_date: 2021-07-06
date_created: 2022-03-18T08:21:47Z
date_published: 2021-07-01T00:00:00Z
date_updated: 2022-03-18T08:45:46Z
day: '01'
department:
- _id: DaAl
doi: 10.1145/3409964.3461810
external_id:
arxiv:
- '2105.08098'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2105.08098
month: '07'
oa: 1
oa_version: Preprint
page: 208-220
publication: Proceedings of the 33rd ACM Symposium on Parallelism in Algorithms and
Architectures
publication_identifier:
isbn:
- '9781450380706'
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
scopus_import: '1'
status: public
title: A scalable concurrent algorithm for dynamic connectivity
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2021'
...
---
_id: '10854'
abstract:
- lang: eng
text: "Consider a distributed task where the communication network is fixed but
the local inputs given to the nodes of the distributed system may change over
time. In this work, we explore the following question: if some of the local inputs
change, can an existing solution be updated efficiently, in a dynamic and distributed
manner?\r\nTo address this question, we define the batch dynamic CONGEST model
in which we are given a bandwidth-limited communication network and a dynamic
edge labelling defines the problem input. The task is to maintain a solution to
a graph problem on the labelled graph under batch changes. We investigate, when
a batch of alpha edge label changes arrive, - how much time as a function of alpha
we need to update an existing solution, and - how much information the nodes have
to keep in local memory between batches in order to update the solution quickly.\r\nOur
work lays the foundations for the theory of input-dynamic distributed network
algorithms. We give a general picture of the complexity landscape in this model,
design both universal algorithms and algorithms for concrete problems, and present
a general framework for lower bounds. The diverse time complexity of our model
spans from constant time, through time polynomial in alpha, and to alpha time,
which we show to be enough for any task."
acknowledgement: We thank Jukka Suomela for discussions. We also thank our shepherd
Mohammad Hajiesmaili and the reviewers for their time and suggestions on how to
improve the paper. This project has received funding from the European Research
Council (ERC) under the European Union’s Horizon 2020 research and innovation programme
(grant agreement No 805223 ScaleML), from the European Union’s Horizon 2020 research
and innovation programme under the Marie Skłodowska–Curie grant agreement No. 840605,
from the Vienna Science and Technology Fund (WWTF) project WHATIF, ICT19-045, 2020-2024,
and from the Austrian Science Fund (FWF) and netIDEE SCIENCE project P 33775-N.
article_processing_charge: No
arxiv: 1
author:
- first_name: Klaus-Tycho
full_name: Foerster, Klaus-Tycho
last_name: Foerster
- first_name: Janne
full_name: Korhonen, Janne
id: C5402D42-15BC-11E9-A202-CA2BE6697425
last_name: Korhonen
- first_name: Ami
full_name: Paz, Ami
last_name: Paz
- first_name: Joel
full_name: Rybicki, Joel
id: 334EFD2E-F248-11E8-B48F-1D18A9856A87
last_name: Rybicki
orcid: 0000-0002-6432-6646
- first_name: Stefan
full_name: Schmid, Stefan
last_name: Schmid
citation:
ama: 'Foerster K-T, Korhonen J, Paz A, Rybicki J, Schmid S. Input-dynamic distributed
algorithms for communication networks. In: Abstract Proceedings of the 2021
ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer
Systems. Association for Computing Machinery; 2021:71-72. doi:10.1145/3410220.3453923'
apa: 'Foerster, K.-T., Korhonen, J., Paz, A., Rybicki, J., & Schmid, S. (2021).
Input-dynamic distributed algorithms for communication networks. In Abstract
Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement
and Modeling of Computer Systems (pp. 71–72). Virtual, Online: Association
for Computing Machinery. https://doi.org/10.1145/3410220.3453923'
chicago: Foerster, Klaus-Tycho, Janne Korhonen, Ami Paz, Joel Rybicki, and Stefan
Schmid. “Input-Dynamic Distributed Algorithms for Communication Networks.” In
Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference
on Measurement and Modeling of Computer Systems, 71–72. Association for Computing
Machinery, 2021. https://doi.org/10.1145/3410220.3453923.
ieee: K.-T. Foerster, J. Korhonen, A. Paz, J. Rybicki, and S. Schmid, “Input-dynamic
distributed algorithms for communication networks,” in Abstract Proceedings
of the 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling
of Computer Systems, Virtual, Online, 2021, pp. 71–72.
ista: 'Foerster K-T, Korhonen J, Paz A, Rybicki J, Schmid S. 2021. Input-dynamic
distributed algorithms for communication networks. Abstract Proceedings of the
2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of
Computer Systems. SIGMETRICS: International Conference on Measurement and Modeling
of Computer Systems, 71–72.'
mla: Foerster, Klaus-Tycho, et al. “Input-Dynamic Distributed Algorithms for Communication
Networks.” Abstract Proceedings of the 2021 ACM SIGMETRICS / International
Conference on Measurement and Modeling of Computer Systems, Association for
Computing Machinery, 2021, pp. 71–72, doi:10.1145/3410220.3453923.
short: K.-T. Foerster, J. Korhonen, A. Paz, J. Rybicki, S. Schmid, in:, Abstract
Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement
and Modeling of Computer Systems, Association for Computing Machinery, 2021, pp.
71–72.
conference:
end_date: 2021-06-18
location: Virtual, Online
name: 'SIGMETRICS: International Conference on Measurement and Modeling of Computer
Systems'
start_date: 2021-06-14
date_created: 2022-03-18T08:48:41Z
date_published: 2021-05-01T00:00:00Z
date_updated: 2023-09-26T10:40:55Z
day: '01'
department:
- _id: DaAl
doi: 10.1145/3410220.3453923
ec_funded: 1
external_id:
arxiv:
- '2005.07637'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2005.07637
month: '05'
oa: 1
oa_version: Preprint
page: 71-72
project:
- _id: 268A44D6-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '805223'
name: Elastic Coordination for Scalable Machine Learning
- _id: 26A5D39A-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '840605'
name: Coordination in constrained and natural distributed systems
publication: Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference
on Measurement and Modeling of Computer Systems
publication_identifier:
isbn:
- '9781450380720'
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
related_material:
record:
- id: '10855'
relation: extended_version
status: public
scopus_import: '1'
status: public
title: Input-dynamic distributed algorithms for communication networks
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2021'
...
---
_id: '10855'
abstract:
- lang: eng
text: 'Consider a distributed task where the communication network is fixed but
the local inputs given to the nodes of the distributed system may change over
time. In this work, we explore the following question: if some of the local inputs
change, can an existing solution be updated efficiently, in a dynamic and distributed
manner? To address this question, we define the batch dynamic \congest model in
which we are given a bandwidth-limited communication network and a dynamic edge
labelling defines the problem input. The task is to maintain a solution to a graph
problem on the labeled graph under batch changes. We investigate, when a batch
of α edge label changes arrive, \beginitemize \item how much time as a function
of α we need to update an existing solution, and \item how much information the
nodes have to keep in local memory between batches in order to update the solution
quickly. \enditemize Our work lays the foundations for the theory of input-dynamic
distributed network algorithms. We give a general picture of the complexity landscape
in this model, design both universal algorithms and algorithms for concrete problems,
and present a general framework for lower bounds. In particular, we derive non-trivial
upper bounds for two selected, contrasting problems: maintaining a minimum spanning
tree and detecting cliques.'
acknowledgement: "We thank Jukka Suomela for discussions. We also thank our shepherd
Mohammad Hajiesmaili\r\nand the reviewers for their time and suggestions on how
to improve the paper. This project\r\nhas received funding from the European Research
Council (ERC) under the European Union’s\r\nHorizon 2020 research and innovation
programme (grant agreement No 805223 ScaleML), from the European Union’s Horizon
2020 research and innovation programme under the Marie\r\nSk lodowska–Curie grant
agreement No. 840605, from the Vienna Science and Technology Fund (WWTF) project
WHATIF, ICT19-045, 2020-2024, and from the Austrian Science Fund (FWF) and netIDEE
SCIENCE project P 33775-N."
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Klaus-Tycho
full_name: Foerster, Klaus-Tycho
last_name: Foerster
- first_name: Janne
full_name: Korhonen, Janne
id: C5402D42-15BC-11E9-A202-CA2BE6697425
last_name: Korhonen
- first_name: Ami
full_name: Paz, Ami
last_name: Paz
- first_name: Joel
full_name: Rybicki, Joel
id: 334EFD2E-F248-11E8-B48F-1D18A9856A87
last_name: Rybicki
orcid: 0000-0002-6432-6646
- first_name: Stefan
full_name: Schmid, Stefan
last_name: Schmid
citation:
ama: Foerster K-T, Korhonen J, Paz A, Rybicki J, Schmid S. Input-dynamic distributed
algorithms for communication networks. Proceedings of the ACM on Measurement
and Analysis of Computing Systems. 2021;5(1):1-33. doi:10.1145/3447384
apa: Foerster, K.-T., Korhonen, J., Paz, A., Rybicki, J., & Schmid, S. (2021).
Input-dynamic distributed algorithms for communication networks. Proceedings
of the ACM on Measurement and Analysis of Computing Systems. Association for
Computing Machinery. https://doi.org/10.1145/3447384
chicago: Foerster, Klaus-Tycho, Janne Korhonen, Ami Paz, Joel Rybicki, and Stefan
Schmid. “Input-Dynamic Distributed Algorithms for Communication Networks.” Proceedings
of the ACM on Measurement and Analysis of Computing Systems. Association for
Computing Machinery, 2021. https://doi.org/10.1145/3447384.
ieee: K.-T. Foerster, J. Korhonen, A. Paz, J. Rybicki, and S. Schmid, “Input-dynamic
distributed algorithms for communication networks,” Proceedings of the ACM
on Measurement and Analysis of Computing Systems, vol. 5, no. 1. Association
for Computing Machinery, pp. 1–33, 2021.
ista: Foerster K-T, Korhonen J, Paz A, Rybicki J, Schmid S. 2021. Input-dynamic
distributed algorithms for communication networks. Proceedings of the ACM on Measurement
and Analysis of Computing Systems. 5(1), 1–33.
mla: Foerster, Klaus-Tycho, et al. “Input-Dynamic Distributed Algorithms for Communication
Networks.” Proceedings of the ACM on Measurement and Analysis of Computing
Systems, vol. 5, no. 1, Association for Computing Machinery, 2021, pp. 1–33,
doi:10.1145/3447384.
short: K.-T. Foerster, J. Korhonen, A. Paz, J. Rybicki, S. Schmid, Proceedings of
the ACM on Measurement and Analysis of Computing Systems 5 (2021) 1–33.
date_created: 2022-03-18T09:10:27Z
date_published: 2021-03-01T00:00:00Z
date_updated: 2023-09-26T10:40:55Z
day: '01'
department:
- _id: DaAl
doi: 10.1145/3447384
ec_funded: 1
external_id:
arxiv:
- '2005.07637'
intvolume: ' 5'
issue: '1'
keyword:
- Computer Networks and Communications
- Hardware and Architecture
- Safety
- Risk
- Reliability and Quality
- Computer Science (miscellaneous)
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2005.07637
month: '03'
oa: 1
oa_version: Preprint
page: 1-33
project:
- _id: 26A5D39A-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '840605'
name: Coordination in constrained and natural distributed systems
- _id: 268A44D6-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '805223'
name: Elastic Coordination for Scalable Machine Learning
publication: Proceedings of the ACM on Measurement and Analysis of Computing Systems
publication_identifier:
issn:
- 2476-1249
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
related_material:
record:
- id: '10854'
relation: shorter_version
status: public
scopus_import: '1'
status: public
title: Input-dynamic distributed algorithms for communication networks
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 5
year: '2021'
...
---
_id: '10856'
abstract:
- lang: eng
text: "We study the properties of the maximal volume k-dimensional sections of the
n-dimensional cube [−1, 1]n. We obtain a first order necessary condition for a
k-dimensional subspace to be a local maximizer of the volume of such sections,
which we formulate in a geometric way. We estimate the length of the projection
of a vector of the standard basis of Rn onto a k-dimensional subspace that maximizes
the volume of the intersection. We \x1Cnd the optimal upper bound on the volume
of a planar section of the cube [−1, 1]n , n ≥ 2."
acknowledgement: "The authors acknowledge the support of the grant of the Russian
Government N 075-15-\r\n2019-1926. G.I.was supported also by the SwissNational Science
Foundation grant 200021-179133. The authors are very grateful to the anonymous reviewer
for valuable remarks."
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Grigory
full_name: Ivanov, Grigory
id: 87744F66-5C6F-11EA-AFE0-D16B3DDC885E
last_name: Ivanov
- first_name: Igor
full_name: Tsiutsiurupa, Igor
last_name: Tsiutsiurupa
citation:
ama: Ivanov G, Tsiutsiurupa I. On the volume of sections of the cube. Analysis
and Geometry in Metric Spaces. 2021;9(1):1-18. doi:10.1515/agms-2020-0103
apa: Ivanov, G., & Tsiutsiurupa, I. (2021). On the volume of sections of the
cube. Analysis and Geometry in Metric Spaces. De Gruyter. https://doi.org/10.1515/agms-2020-0103
chicago: Ivanov, Grigory, and Igor Tsiutsiurupa. “On the Volume of Sections of the
Cube.” Analysis and Geometry in Metric Spaces. De Gruyter, 2021. https://doi.org/10.1515/agms-2020-0103.
ieee: G. Ivanov and I. Tsiutsiurupa, “On the volume of sections of the cube,” Analysis
and Geometry in Metric Spaces, vol. 9, no. 1. De Gruyter, pp. 1–18, 2021.
ista: Ivanov G, Tsiutsiurupa I. 2021. On the volume of sections of the cube. Analysis
and Geometry in Metric Spaces. 9(1), 1–18.
mla: Ivanov, Grigory, and Igor Tsiutsiurupa. “On the Volume of Sections of the Cube.”
Analysis and Geometry in Metric Spaces, vol. 9, no. 1, De Gruyter, 2021,
pp. 1–18, doi:10.1515/agms-2020-0103.
short: G. Ivanov, I. Tsiutsiurupa, Analysis and Geometry in Metric Spaces 9 (2021)
1–18.
date_created: 2022-03-18T09:25:14Z
date_published: 2021-01-29T00:00:00Z
date_updated: 2023-08-17T07:07:58Z
day: '29'
ddc:
- '510'
department:
- _id: UlWa
doi: 10.1515/agms-2020-0103
external_id:
arxiv:
- '2004.02674'
isi:
- '000734286800001'
file:
- access_level: open_access
checksum: 7e615ac8489f5eae580b6517debfdc53
content_type: application/pdf
creator: dernst
date_created: 2022-03-18T09:31:59Z
date_updated: 2022-03-18T09:31:59Z
file_id: '10857'
file_name: 2021_AnalysisMetricSpaces_Ivanov.pdf
file_size: 789801
relation: main_file
success: 1
file_date_updated: 2022-03-18T09:31:59Z
has_accepted_license: '1'
intvolume: ' 9'
isi: 1
issue: '1'
keyword:
- Applied Mathematics
- Geometry and Topology
- Analysis
language:
- iso: eng
month: '01'
oa: 1
oa_version: Published Version
page: 1-18
publication: Analysis and Geometry in Metric Spaces
publication_identifier:
issn:
- 2299-3274
publication_status: published
publisher: De Gruyter
quality_controlled: '1'
scopus_import: '1'
status: public
title: On the volume of sections of the cube
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 9
year: '2021'
...
---
_id: '10858'
abstract:
- lang: eng
text: The cost-effective conversion of low-grade heat into electricity using thermoelectric
devices requires developing alternative materials and material processing technologies
able to reduce the currently high device manufacturing costs. In this direction,
thermoelectric materials that do not rely on rare or toxic elements such as tellurium
or lead need to be produced using high-throughput technologies not involving high
temperatures and long processes. Bi2Se3 is an obvious possible Te-free alternative
to Bi2Te3 for ambient temperature thermoelectric applications, but its performance
is still low for practical applications, and additional efforts toward finding
proper dopants are required. Here, we report a scalable method to produce Bi2Se3
nanosheets at low synthesis temperatures. We studied the influence of different
dopants on the thermoelectric properties of this material. Among the elements
tested, we demonstrated that Sn doping resulted in the best performance. Sn incorporation
resulted in a significant improvement to the Bi2Se3 Seebeck coefficient and a
reduction in the thermal conductivity in the direction of the hot-press axis,
resulting in an overall 60% improvement in the thermoelectric figure of merit
of Bi2Se3.
acknowledgement: "M.L., Y.Z., T.Z. and K.X. thank the China Scholarship Council for
their scholarship\r\nsupport. Y.L. acknowledges funding from the European Union’s
Horizon 2020 research and\r\ninnovation program under the Marie Sklodowska-Curie
grant agreement No. 754411. J.L. thanks the ICREA Academia program and projects
MICINN/FEDER RTI2018-093996-B-C31 and G.C. 2017 SGR 128. ICN2 acknowledges funding
from the Generalitat de Catalunya 2017 SGR 327 and the Spanish MINECO ENE2017-85087-C3."
article_number: '1827'
article_processing_charge: No
article_type: original
author:
- first_name: Mengyao
full_name: Li, Mengyao
last_name: Li
- first_name: Yu
full_name: Zhang, Yu
last_name: Zhang
- first_name: Ting
full_name: Zhang, Ting
last_name: Zhang
- first_name: Yong
full_name: Zuo, Yong
last_name: Zuo
- first_name: Ke
full_name: Xiao, Ke
last_name: Xiao
- first_name: Jordi
full_name: Arbiol, Jordi
last_name: Arbiol
- first_name: Jordi
full_name: Llorca, Jordi
last_name: Llorca
- first_name: Yu
full_name: Liu, Yu
id: 2A70014E-F248-11E8-B48F-1D18A9856A87
last_name: Liu
orcid: 0000-0001-7313-6740
- first_name: Andreu
full_name: Cabot, Andreu
last_name: Cabot
citation:
ama: Li M, Zhang Y, Zhang T, et al. Enhanced thermoelectric performance of n-type
Bi2Se3 nanosheets through Sn doping. Nanomaterials. 2021;11(7). doi:10.3390/nano11071827
apa: Li, M., Zhang, Y., Zhang, T., Zuo, Y., Xiao, K., Arbiol, J., … Cabot, A. (2021).
Enhanced thermoelectric performance of n-type Bi2Se3 nanosheets through Sn doping.
Nanomaterials. MDPI. https://doi.org/10.3390/nano11071827
chicago: Li, Mengyao, Yu Zhang, Ting Zhang, Yong Zuo, Ke Xiao, Jordi Arbiol, Jordi
Llorca, Yu Liu, and Andreu Cabot. “Enhanced Thermoelectric Performance of N-Type
Bi2Se3 Nanosheets through Sn Doping.” Nanomaterials. MDPI, 2021. https://doi.org/10.3390/nano11071827.
ieee: M. Li et al., “Enhanced thermoelectric performance of n-type Bi2Se3
nanosheets through Sn doping,” Nanomaterials, vol. 11, no. 7. MDPI, 2021.
ista: Li M, Zhang Y, Zhang T, Zuo Y, Xiao K, Arbiol J, Llorca J, Liu Y, Cabot A.
2021. Enhanced thermoelectric performance of n-type Bi2Se3 nanosheets through
Sn doping. Nanomaterials. 11(7), 1827.
mla: Li, Mengyao, et al. “Enhanced Thermoelectric Performance of N-Type Bi2Se3 Nanosheets
through Sn Doping.” Nanomaterials, vol. 11, no. 7, 1827, MDPI, 2021, doi:10.3390/nano11071827.
short: M. Li, Y. Zhang, T. Zhang, Y. Zuo, K. Xiao, J. Arbiol, J. Llorca, Y. Liu,
A. Cabot, Nanomaterials 11 (2021).
date_created: 2022-03-18T09:45:02Z
date_published: 2021-07-14T00:00:00Z
date_updated: 2023-08-17T07:08:30Z
day: '14'
ddc:
- '540'
department:
- _id: MaIb
doi: 10.3390/nano11071827
ec_funded: 1
external_id:
isi:
- '000676570000001'
file:
- access_level: open_access
checksum: f28a8b5cf80f5605828359bb398463b0
content_type: application/pdf
creator: dernst
date_created: 2022-03-18T09:53:15Z
date_updated: 2022-03-18T09:53:15Z
file_id: '10859'
file_name: 2021_Nanomaterials_Li.pdf
file_size: 4867547
relation: main_file
success: 1
file_date_updated: 2022-03-18T09:53:15Z
has_accepted_license: '1'
intvolume: ' 11'
isi: 1
issue: '7'
keyword:
- General Materials Science
- General Chemical Engineering
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
publication: Nanomaterials
publication_identifier:
issn:
- 2079-4991
publication_status: published
publisher: MDPI
quality_controlled: '1'
scopus_import: '1'
status: public
title: Enhanced thermoelectric performance of n-type Bi2Se3 nanosheets through Sn
doping
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 11
year: '2021'
...
---
_id: '10860'
abstract:
- lang: eng
text: A tight frame is the orthogonal projection of some orthonormal basis of Rn
onto Rk. We show that a set of vectors is a tight frame if and only if the set
of all cross products of these vectors is a tight frame. We reformulate a range
of problems on the volume of projections (or sections) of regular polytopes in
terms of tight frames and write a first-order necessary condition for local extrema
of these problems. As applications, we prove new results for the problem of maximization
of the volume of zonotopes.
acknowledgement: The author was supported by the Swiss National Science Foundation
grant 200021_179133. The author acknowledges the financial support from the Ministry
of Education and Science of the Russian Federation in the framework of MegaGrant
no. 075-15-2019-1926.
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Grigory
full_name: Ivanov, Grigory
id: 87744F66-5C6F-11EA-AFE0-D16B3DDC885E
last_name: Ivanov
citation:
ama: Ivanov G. Tight frames and related geometric problems. Canadian Mathematical
Bulletin. 2021;64(4):942-963. doi:10.4153/s000843952000096x
apa: Ivanov, G. (2021). Tight frames and related geometric problems. Canadian
Mathematical Bulletin. Canadian Mathematical Society. https://doi.org/10.4153/s000843952000096x
chicago: Ivanov, Grigory. “Tight Frames and Related Geometric Problems.” Canadian
Mathematical Bulletin. Canadian Mathematical Society, 2021. https://doi.org/10.4153/s000843952000096x.
ieee: G. Ivanov, “Tight frames and related geometric problems,” Canadian Mathematical
Bulletin, vol. 64, no. 4. Canadian Mathematical Society, pp. 942–963, 2021.
ista: Ivanov G. 2021. Tight frames and related geometric problems. Canadian Mathematical
Bulletin. 64(4), 942–963.
mla: Ivanov, Grigory. “Tight Frames and Related Geometric Problems.” Canadian
Mathematical Bulletin, vol. 64, no. 4, Canadian Mathematical Society, 2021,
pp. 942–63, doi:10.4153/s000843952000096x.
short: G. Ivanov, Canadian Mathematical Bulletin 64 (2021) 942–963.
date_created: 2022-03-18T09:55:59Z
date_published: 2021-12-18T00:00:00Z
date_updated: 2023-09-05T12:43:09Z
day: '18'
department:
- _id: UlWa
doi: 10.4153/s000843952000096x
external_id:
arxiv:
- '1804.10055'
isi:
- '000730165300021'
intvolume: ' 64'
isi: 1
issue: '4'
keyword:
- General Mathematics
- Tight frame
- Grassmannian
- zonotope
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1804.10055
month: '12'
oa: 1
oa_version: Preprint
page: 942-963
publication: Canadian Mathematical Bulletin
publication_identifier:
eissn:
- 1496-4287
issn:
- 0008-4395
publication_status: published
publisher: Canadian Mathematical Society
quality_controlled: '1'
scopus_import: '1'
status: public
title: Tight frames and related geometric problems
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 64
year: '2021'
...
---
_id: '10912'
abstract:
- lang: eng
text: Brain dynamics display collective phenomena as diverse as neuronal oscillations
and avalanches. Oscillations are rhythmic, with fluctuations occurring at a characteristic
scale, whereas avalanches are scale-free cascades of neural activity. Here we
show that such antithetic features can coexist in a very generic class of adaptive
neural networks. In the most simple yet fully microscopic model from this class
we make direct contact with human brain resting-state activity recordings via
tractable inference of the model's two essential parameters. The inferred model
quantitatively captures the dynamics over a broad range of scales, from single
sensor fluctuations, collective behaviors of nearly-synchronous extreme events
on multiple sensors, to neuronal avalanches unfolding over multiple sensors across
multiple time-bins. Importantly, the inferred parameters correlate with model-independent
signatures of "closeness to criticality", suggesting that the coexistence of scale-specific
(neural oscillations) and scale-free (neuronal avalanches) dynamics in brain activity
occurs close to a non-equilibrium critical point at the onset of self-sustained
oscillations.
acknowledgement: "FL acknowledges support from the European Union’s Horizon 2020 research
and innovation program under the Marie Sklodowska-Curie Grant Agreement No. 754411.
GT\r\nacknowledges the support of the Austrian Science Fund (FWF) under Stand-Alone
Grant\r\nNo. P34015."
article_processing_charge: No
arxiv: 1
author:
- first_name: Fabrizio
full_name: Lombardi, Fabrizio
id: A057D288-3E88-11E9-986D-0CF4E5697425
last_name: Lombardi
orcid: 0000-0003-2623-5249
- first_name: Selver
full_name: Pepic, Selver
id: F93245C4-C3CA-11E9-B4F0-C6F4E5697425
last_name: Pepic
- first_name: Oren
full_name: Shriki, Oren
last_name: Shriki
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
- first_name: Daniele
full_name: De Martino, Daniele
last_name: De Martino
citation:
ama: Lombardi F, Pepic S, Shriki O, Tkačik G, De Martino D. Quantifying the coexistence
of neuronal oscillations and avalanches. doi:10.48550/ARXIV.2108.06686
apa: Lombardi, F., Pepic, S., Shriki, O., Tkačik, G., & De Martino, D. (n.d.).
Quantifying the coexistence of neuronal oscillations and avalanches. arXiv. https://doi.org/10.48550/ARXIV.2108.06686
chicago: Lombardi, Fabrizio, Selver Pepic, Oren Shriki, Gašper Tkačik, and Daniele
De Martino. “Quantifying the Coexistence of Neuronal Oscillations and Avalanches.”
arXiv, n.d. https://doi.org/10.48550/ARXIV.2108.06686.
ieee: F. Lombardi, S. Pepic, O. Shriki, G. Tkačik, and D. De Martino, “Quantifying
the coexistence of neuronal oscillations and avalanches.” arXiv.
ista: Lombardi F, Pepic S, Shriki O, Tkačik G, De Martino D. Quantifying the coexistence
of neuronal oscillations and avalanches. 10.48550/ARXIV.2108.06686.
mla: Lombardi, Fabrizio, et al. Quantifying the Coexistence of Neuronal Oscillations
and Avalanches. arXiv, doi:10.48550/ARXIV.2108.06686.
short: F. Lombardi, S. Pepic, O. Shriki, G. Tkačik, D. De Martino, (n.d.).
date_created: 2022-03-21T11:41:28Z
date_published: 2021-08-17T00:00:00Z
date_updated: 2022-03-22T07:53:18Z
day: '17'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.48550/ARXIV.2108.06686
ec_funded: 1
external_id:
arxiv:
- '2108.06686'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2108.06686
month: '08'
oa: 1
oa_version: Preprint
page: '37'
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
- _id: 626c45b5-2b32-11ec-9570-e509828c1ba6
grant_number: P34015
name: Efficient coding with biophysical realism
publication_status: submitted
publisher: arXiv
status: public
title: Quantifying the coexistence of neuronal oscillations and avalanches
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2021'
...
---
_id: '11436'
abstract:
- lang: eng
text: Asynchronous distributed algorithms are a popular way to reduce synchronization
costs in large-scale optimization, and in particular for neural network training.
However, for nonsmooth and nonconvex objectives, few convergence guarantees exist
beyond cases where closed-form proximal operator solutions are available. As training
most popular deep neural networks corresponds to optimizing nonsmooth and nonconvex
objectives, there is a pressing need for such convergence guarantees. In this
paper, we analyze for the first time the convergence of stochastic asynchronous
optimization for this general class of objectives. In particular, we focus on
stochastic subgradient methods allowing for block variable partitioning, where
the shared model is asynchronously updated by concurrent processes. To this end,
we use a probabilistic model which captures key features of real asynchronous
scheduling between concurrent processes. Under this model, we establish convergence
with probability one to an invariant set for stochastic subgradient methods with
momentum. From a practical perspective, one issue with the family of algorithms
that we consider is that they are not efficiently supported by machine learning
frameworks, which mostly focus on distributed data-parallel strategies. To address
this, we propose a new implementation strategy for shared-memory based training
of deep neural networks for a partitioned but shared model in single- and multi-GPU
settings. Based on this implementation, we achieve on average1.2x speed-up in
comparison to state-of-the-art training methods for popular image classification
tasks, without compromising accuracy.
acknowledgement: Vyacheslav Kungurtsev was supported by the OP VVV project CZ.02.1.01/0.0/0.0/16
019/0000765 “Research Center for Informatics. Bapi Chatterjee was supported by the
European Union’s Horizon 2020 research and innovation programme under the Marie
Sklodowska-Curie grant agreement No. 754411 (ISTPlus). Dan Alistarh has received
funding from the European Research Council (ERC) under the European Union’s Horizon
2020 research and innovation programme (grant agreement No 805223 ScaleML).
article_processing_charge: No
arxiv: 1
author:
- first_name: Vyacheslav
full_name: Kungurtsev, Vyacheslav
last_name: Kungurtsev
- first_name: Malcolm
full_name: Egan, Malcolm
last_name: Egan
- first_name: Bapi
full_name: Chatterjee, Bapi
id: 3C41A08A-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
- first_name: Dan-Adrian
full_name: Alistarh, Dan-Adrian
id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
last_name: Alistarh
orcid: 0000-0003-3650-940X
citation:
ama: 'Kungurtsev V, Egan M, Chatterjee B, Alistarh D-A. Asynchronous optimization
methods for efficient training of deep neural networks with guarantees. In: 35th
AAAI Conference on Artificial Intelligence, AAAI 2021. Vol 35. AAAI Press;
2021:8209-8216.'
apa: 'Kungurtsev, V., Egan, M., Chatterjee, B., & Alistarh, D.-A. (2021). Asynchronous
optimization methods for efficient training of deep neural networks with guarantees.
In 35th AAAI Conference on Artificial Intelligence, AAAI 2021 (Vol. 35,
pp. 8209–8216). Virtual, Online: AAAI Press.'
chicago: Kungurtsev, Vyacheslav, Malcolm Egan, Bapi Chatterjee, and Dan-Adrian Alistarh.
“Asynchronous Optimization Methods for Efficient Training of Deep Neural Networks
with Guarantees.” In 35th AAAI Conference on Artificial Intelligence, AAAI
2021, 35:8209–16. AAAI Press, 2021.
ieee: V. Kungurtsev, M. Egan, B. Chatterjee, and D.-A. Alistarh, “Asynchronous optimization
methods for efficient training of deep neural networks with guarantees,” in 35th
AAAI Conference on Artificial Intelligence, AAAI 2021, Virtual, Online, 2021,
vol. 35, no. 9B, pp. 8209–8216.
ista: 'Kungurtsev V, Egan M, Chatterjee B, Alistarh D-A. 2021. Asynchronous optimization
methods for efficient training of deep neural networks with guarantees. 35th AAAI
Conference on Artificial Intelligence, AAAI 2021. AAAI: Conference on Artificial
Intelligence vol. 35, 8209–8216.'
mla: Kungurtsev, Vyacheslav, et al. “Asynchronous Optimization Methods for Efficient
Training of Deep Neural Networks with Guarantees.” 35th AAAI Conference on
Artificial Intelligence, AAAI 2021, vol. 35, no. 9B, AAAI Press, 2021, pp.
8209–16.
short: V. Kungurtsev, M. Egan, B. Chatterjee, D.-A. Alistarh, in:, 35th AAAI Conference
on Artificial Intelligence, AAAI 2021, AAAI Press, 2021, pp. 8209–8216.
conference:
end_date: 2021-02-09
location: Virtual, Online
name: 'AAAI: Conference on Artificial Intelligence'
start_date: 2021-02-02
date_created: 2022-06-05T22:01:52Z
date_published: 2021-05-18T00:00:00Z
date_updated: 2022-06-07T06:53:36Z
day: '18'
department:
- _id: DaAl
ec_funded: 1
external_id:
arxiv:
- '1905.11845'
intvolume: ' 35'
issue: 9B
language:
- iso: eng
main_file_link:
- open_access: '1'
url: ' https://doi.org/10.48550/arXiv.1905.11845'
month: '05'
oa: 1
oa_version: Preprint
page: 8209-8216
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
- _id: 268A44D6-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '805223'
name: Elastic Coordination for Scalable Machine Learning
publication: 35th AAAI Conference on Artificial Intelligence, AAAI 2021
publication_identifier:
eissn:
- 2374-3468
isbn:
- '9781713835974'
issn:
- 2159-5399
publication_status: published
publisher: AAAI Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: Asynchronous optimization methods for efficient training of deep neural networks
with guarantees
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 35
year: '2021'
...
---
_id: '11452'
abstract:
- lang: eng
text: We study efficient distributed algorithms for the fundamental problem of principal
component analysis and leading eigenvector computation on the sphere, when the
data are randomly distributed among a set of computational nodes. We propose a
new quantized variant of Riemannian gradient descent to solve this problem, and
prove that the algorithm converges with high probability under a set of necessary
spherical-convexity properties. We give bounds on the number of bits transmitted
by the algorithm under common initialization schemes, and investigate the dependency
on the problem dimension in each case.
acknowledgement: We would like to thank the anonymous reviewers for helpful comments
and suggestions. We also thank Aurelien Lucchi and Antonio Orvieto for fruitful
discussions at an early stage of this work. FA is partially supported by the SNSF
under research project No. 192363 and conducted part of this work while at IST Austria
under the European Union’s Horizon 2020 research and innovation programme (grant
agreement No. 805223 ScaleML). PD partly conducted this work while at IST Austria
and was supported by the European Union’s Horizon 2020 programme under the Marie
Skłodowska-Curie grant agreement No. 754411.
article_processing_charge: No
arxiv: 1
author:
- first_name: Foivos
full_name: Alimisis, Foivos
last_name: Alimisis
- first_name: Peter
full_name: Davies, Peter
id: 11396234-BB50-11E9-B24C-90FCE5697425
last_name: Davies
orcid: 0000-0002-5646-9524
- first_name: Bart
full_name: Vandereycken, Bart
last_name: Vandereycken
- first_name: Dan-Adrian
full_name: Alistarh, Dan-Adrian
id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
last_name: Alistarh
orcid: 0000-0003-3650-940X
citation:
ama: 'Alimisis F, Davies P, Vandereycken B, Alistarh D-A. Distributed principal
component analysis with limited communication. In: Advances in Neural Information
Processing Systems - 35th Conference on Neural Information Processing Systems.
Vol 4. Neural Information Processing Systems Foundation; 2021:2823-2834.'
apa: 'Alimisis, F., Davies, P., Vandereycken, B., & Alistarh, D.-A. (2021).
Distributed principal component analysis with limited communication. In Advances
in Neural Information Processing Systems - 35th Conference on Neural Information
Processing Systems (Vol. 4, pp. 2823–2834). Virtual, Online: Neural Information
Processing Systems Foundation.'
chicago: Alimisis, Foivos, Peter Davies, Bart Vandereycken, and Dan-Adrian Alistarh.
“Distributed Principal Component Analysis with Limited Communication.” In Advances
in Neural Information Processing Systems - 35th Conference on Neural Information
Processing Systems, 4:2823–34. Neural Information Processing Systems Foundation,
2021.
ieee: F. Alimisis, P. Davies, B. Vandereycken, and D.-A. Alistarh, “Distributed
principal component analysis with limited communication,” in Advances in Neural
Information Processing Systems - 35th Conference on Neural Information Processing
Systems, Virtual, Online, 2021, vol. 4, pp. 2823–2834.
ista: 'Alimisis F, Davies P, Vandereycken B, Alistarh D-A. 2021. Distributed principal
component analysis with limited communication. Advances in Neural Information
Processing Systems - 35th Conference on Neural Information Processing Systems.
NeurIPS: Neural Information Processing Systems vol. 4, 2823–2834.'
mla: Alimisis, Foivos, et al. “Distributed Principal Component Analysis with Limited
Communication.” Advances in Neural Information Processing Systems - 35th Conference
on Neural Information Processing Systems, vol. 4, Neural Information Processing
Systems Foundation, 2021, pp. 2823–34.
short: F. Alimisis, P. Davies, B. Vandereycken, D.-A. Alistarh, in:, Advances in
Neural Information Processing Systems - 35th Conference on Neural Information
Processing Systems, Neural Information Processing Systems Foundation, 2021, pp.
2823–2834.
conference:
end_date: 2021-12-14
location: Virtual, Online
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2021-12-06
date_created: 2022-06-19T22:01:58Z
date_published: 2021-12-01T00:00:00Z
date_updated: 2022-06-20T08:31:52Z
day: '01'
department:
- _id: DaAl
ec_funded: 1
external_id:
arxiv:
- '2110.14391'
intvolume: ' 4'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://proceedings.neurips.cc/paper/2021/file/1680e9fa7b4dd5d62ece800239bb53bd-Paper.pdf
month: '12'
oa: 1
oa_version: Published Version
page: 2823-2834
project:
- _id: 268A44D6-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '805223'
name: Elastic Coordination for Scalable Machine Learning
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
publication: Advances in Neural Information Processing Systems - 35th Conference on
Neural Information Processing Systems
publication_identifier:
isbn:
- '9781713845393'
issn:
- 1049-5258
publication_status: published
publisher: Neural Information Processing Systems Foundation
quality_controlled: '1'
scopus_import: '1'
status: public
title: Distributed principal component analysis with limited communication
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 4
year: '2021'
...
---
_id: '11453'
abstract:
- lang: eng
text: "Neuronal computations depend on synaptic connectivity and intrinsic electrophysiological
properties. Synaptic connectivity determines which inputs from presynaptic neurons
are integrated, while cellular properties determine how inputs are filtered over
time. Unlike their biological counterparts, most computational approaches to learning
in simulated neural networks are limited to changes in synaptic connectivity.
However, if intrinsic parameters change, neural computations are altered drastically.
Here, we include the parameters that determine the intrinsic properties,\r\ne.g.,
time constants and reset potential, into the learning paradigm. Using sparse feedback
signals that indicate target spike times, and gradient-based parameter updates,
we show that the intrinsic parameters can be learned along with the synaptic weights
to produce specific input-output functions. Specifically, we use a teacher-student
paradigm in which a randomly initialised leaky integrate-and-fire or resonate-and-fire
neuron must recover the parameters of a teacher neuron. We show that complex temporal
functions can be learned online and without backpropagation through time, relying
on event-based updates only. Our results are a step towards online learning of
neural computations from ungraded and unsigned sparse feedback signals with a
biologically inspired learning mechanism."
acknowledgement: We would like to thank Professor Dr. Henning Sprekeler for his valuable
suggestions and Dr. Andrew Saxe, Milan Klöwer and Anna Wallis for their constructive
feedback on the manuscript. Lukas Braun was supported by the Network of European
Neuroscience Schools through their NENS Exchange Grant program, by the European
Union through their European Community Action Scheme for the Mobility of University
Students, the Woodward Scholarship awarded by Wadham College, Oxford and the Medical
Research Council [MR/N013468/1]. Tim P. Vogels was supported by a Wellcome Trust
Senior Research Fellowship [214316/Z/18/Z].
article_processing_charge: No
author:
- first_name: Lukas
full_name: Braun, Lukas
last_name: Braun
- first_name: Tim P
full_name: Vogels, Tim P
id: CB6FF8D2-008F-11EA-8E08-2637E6697425
last_name: Vogels
orcid: 0000-0003-3295-6181
citation:
ama: 'Braun L, Vogels TP. Online learning of neural computations from sparse temporal
feedback. In: Advances in Neural Information Processing Systems - 35th Conference
on Neural Information Processing Systems. Vol 20. Neural Information Processing
Systems Foundation; 2021:16437-16450.'
apa: 'Braun, L., & Vogels, T. P. (2021). Online learning of neural computations
from sparse temporal feedback. In Advances in Neural Information Processing
Systems - 35th Conference on Neural Information Processing Systems (Vol. 20,
pp. 16437–16450). Virtual, Online: Neural Information Processing Systems Foundation.'
chicago: Braun, Lukas, and Tim P Vogels. “Online Learning of Neural Computations
from Sparse Temporal Feedback.” In Advances in Neural Information Processing
Systems - 35th Conference on Neural Information Processing Systems, 20:16437–50.
Neural Information Processing Systems Foundation, 2021.
ieee: L. Braun and T. P. Vogels, “Online learning of neural computations from sparse
temporal feedback,” in Advances in Neural Information Processing Systems -
35th Conference on Neural Information Processing Systems, Virtual, Online,
2021, vol. 20, pp. 16437–16450.
ista: 'Braun L, Vogels TP. 2021. Online learning of neural computations from sparse
temporal feedback. Advances in Neural Information Processing Systems - 35th Conference
on Neural Information Processing Systems. NeurIPS: Neural Information Processing
Systems vol. 20, 16437–16450.'
mla: Braun, Lukas, and Tim P. Vogels. “Online Learning of Neural Computations from
Sparse Temporal Feedback.” Advances in Neural Information Processing Systems
- 35th Conference on Neural Information Processing Systems, vol. 20, Neural
Information Processing Systems Foundation, 2021, pp. 16437–50.
short: L. Braun, T.P. Vogels, in:, Advances in Neural Information Processing Systems
- 35th Conference on Neural Information Processing Systems, Neural Information
Processing Systems Foundation, 2021, pp. 16437–16450.
conference:
end_date: 2021-12-14
location: Virtual, Online
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2021-12-06
date_created: 2022-06-19T22:01:59Z
date_published: 2021-12-01T00:00:00Z
date_updated: 2022-06-20T07:12:58Z
day: '01'
department:
- _id: TiVo
intvolume: ' 20'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://proceedings.neurips.cc/paper/2021/file/88e1ce84f9feef5a08d0df0334c53468-Paper.pdf
month: '12'
oa: 1
oa_version: Published Version
page: 16437-16450
project:
- _id: c084a126-5a5b-11eb-8a69-d75314a70a87
grant_number: 214316/Z/18/Z
name: What’s in a memory? Spatiotemporal dynamics in strongly coupled recurrent
neuronal networks.
publication: Advances in Neural Information Processing Systems - 35th Conference on
Neural Information Processing Systems
publication_identifier:
isbn:
- '9781713845393'
issn:
- 1049-5258
publication_status: published
publisher: Neural Information Processing Systems Foundation
quality_controlled: '1'
scopus_import: '1'
status: public
title: Online learning of neural computations from sparse temporal feedback
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 20
year: '2021'
...
---
_id: '11458'
abstract:
- lang: eng
text: 'The increasing computational requirements of deep neural networks (DNNs)
have led to significant interest in obtaining DNN models that are sparse, yet
accurate. Recent work has investigated the even harder case of sparse training,
where the DNN weights are, for as much as possible, already sparse to reduce computational
costs during training. Existing sparse training methods are often empirical and
can have lower accuracy relative to the dense baseline. In this paper, we present
a general approach called Alternating Compressed/DeCompressed (AC/DC) training
of DNNs, demonstrate convergence for a variant of the algorithm, and show that
AC/DC outperforms existing sparse training methods in accuracy at similar computational
budgets; at high sparsity levels, AC/DC even outperforms existing methods that
rely on accurate pre-trained dense models. An important property of AC/DC is that
it allows co-training of dense and sparse models, yielding accurate sparse–dense
model pairs at the end of the training process. This is useful in practice, where
compressed variants may be desirable for deployment in resource-constrained settings
without re-doing the entire training flow, and also provides us with insights
into the accuracy gap between dense and compressed models. The code is available
at: https://github.com/IST-DASLab/ACDC.'
acknowledged_ssus:
- _id: ScienComp
acknowledgement: This project has received funding from the European Research Council
(ERC) under the European Union’s Horizon 2020 research and innovation programme
(grant agreement No 805223 ScaleML), and a CNRS PEPS grant. This research was supported
by the Scientific Service Units (SSU) of IST Austria through resources provided
by Scientific Computing (SciComp). We would also like to thank Christoph Lampert
for his feedback on an earlier version of this work, as well as for providing hardware
for the Transformer-XL experiments.
article_processing_charge: No
arxiv: 1
author:
- first_name: Elena-Alexandra
full_name: Peste, Elena-Alexandra
id: 32D78294-F248-11E8-B48F-1D18A9856A87
last_name: Peste
- first_name: Eugenia B
full_name: Iofinova, Eugenia B
id: f9a17499-f6e0-11ea-865d-fdf9a3f77117
last_name: Iofinova
orcid: 0000-0002-7778-3221
- first_name: Adrian
full_name: Vladu, Adrian
last_name: Vladu
- first_name: Dan-Adrian
full_name: Alistarh, Dan-Adrian
id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
last_name: Alistarh
orcid: 0000-0003-3650-940X
citation:
ama: 'Peste E-A, Iofinova EB, Vladu A, Alistarh D-A. AC/DC: Alternating Compressed/DeCompressed
training of deep neural networks. In: 35th Conference on Neural Information
Processing Systems. Vol 34. Curran Associates; 2021:8557-8570.'
apa: 'Peste, E.-A., Iofinova, E. B., Vladu, A., & Alistarh, D.-A. (2021). AC/DC:
Alternating Compressed/DeCompressed training of deep neural networks. In 35th
Conference on Neural Information Processing Systems (Vol. 34, pp. 8557–8570).
Virtual, Online: Curran Associates.'
chicago: 'Peste, Elena-Alexandra, Eugenia B Iofinova, Adrian Vladu, and Dan-Adrian
Alistarh. “AC/DC: Alternating Compressed/DeCompressed Training of Deep Neural
Networks.” In 35th Conference on Neural Information Processing Systems,
34:8557–70. Curran Associates, 2021.'
ieee: 'E.-A. Peste, E. B. Iofinova, A. Vladu, and D.-A. Alistarh, “AC/DC: Alternating
Compressed/DeCompressed training of deep neural networks,” in 35th Conference
on Neural Information Processing Systems, Virtual, Online, 2021, vol. 34,
pp. 8557–8570.'
ista: 'Peste E-A, Iofinova EB, Vladu A, Alistarh D-A. 2021. AC/DC: Alternating Compressed/DeCompressed
training of deep neural networks. 35th Conference on Neural Information Processing
Systems. NeurIPS: Neural Information Processing Systems vol. 34, 8557–8570.'
mla: 'Peste, Elena-Alexandra, et al. “AC/DC: Alternating Compressed/DeCompressed
Training of Deep Neural Networks.” 35th Conference on Neural Information Processing
Systems, vol. 34, Curran Associates, 2021, pp. 8557–70.'
short: E.-A. Peste, E.B. Iofinova, A. Vladu, D.-A. Alistarh, in:, 35th Conference
on Neural Information Processing Systems, Curran Associates, 2021, pp. 8557–8570.
conference:
end_date: 2021-12-14
location: Virtual, Online
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2021-12-06
date_created: 2022-06-20T12:11:53Z
date_published: 2021-12-06T00:00:00Z
date_updated: 2023-06-01T12:54:45Z
day: '6'
department:
- _id: GradSch
- _id: DaAl
ec_funded: 1
external_id:
arxiv:
- '2106.12379'
intvolume: ' 34'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://proceedings.neurips.cc/paper/2021/file/48000647b315f6f00f913caa757a70b3-Paper.pdf
month: '12'
oa: 1
oa_version: Published Version
page: 8557-8570
project:
- _id: 268A44D6-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '805223'
name: Elastic Coordination for Scalable Machine Learning
publication: 35th Conference on Neural Information Processing Systems
publication_identifier:
isbn:
- '9781713845393'
issn:
- 1049-5258
publication_status: published
publisher: Curran Associates
quality_controlled: '1'
related_material:
record:
- id: '13074'
relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: 'AC/DC: Alternating Compressed/DeCompressed training of deep neural networks'
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 34
year: '2021'
...
---
_id: '11463'
abstract:
- lang: eng
text: "Efficiently approximating local curvature information of the loss function
is a key tool for optimization and compression of deep neural networks. Yet, most
existing methods to approximate second-order information have high computational\r\nor
storage costs, which limits their practicality. In this work, we investigate matrix-free,
linear-time approaches for estimating Inverse-Hessian Vector Products (IHVPs)
for the case when the Hessian can be approximated as a sum of rank-one matrices,
as in the classic approximation of the Hessian by the empirical Fisher matrix.
We propose two new algorithms: the first is tailored towards network compression
and can compute the IHVP for dimension d, if the Hessian is given as a sum of
m rank-one matrices, using O(dm2) precomputation, O(dm) cost for computing the
IHVP, and query cost O(m) for any single element of the inverse Hessian. The second
algorithm targets an optimization setting, where we wish to compute the product
between the inverse Hessian, estimated over a sliding window of optimization steps,
and a given gradient direction, as required for preconditioned SGD. We give an
algorithm with cost O(dm + m2) for computing the IHVP and O(dm + m3) for adding
or removing any gradient from the sliding window. These\r\ntwo algorithms yield
state-of-the-art results for network pruning and optimization with lower computational
overhead relative to existing second-order methods. Implementations are available
at [9] and [17]."
acknowledgement: We gratefully acknowledge funding the European Research Council (ERC)
under the European Union’s Horizon 2020 research and innovation programme (grant
agreement No 805223 ScaleML), as well as computational support from Amazon Web Services
(AWS) EC2.
article_processing_charge: No
arxiv: 1
author:
- first_name: Elias
full_name: Frantar, Elias
id: 09a8f98d-ec99-11ea-ae11-c063a7b7fe5f
last_name: Frantar
- first_name: Eldar
full_name: Kurtic, Eldar
id: 47beb3a5-07b5-11eb-9b87-b108ec578218
last_name: Kurtic
- first_name: Dan-Adrian
full_name: Alistarh, Dan-Adrian
id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
last_name: Alistarh
orcid: 0000-0003-3650-940X
citation:
ama: 'Frantar E, Kurtic E, Alistarh D-A. M-FAC: Efficient matrix-free approximations
of second-order information. In: 35th Conference on Neural Information Processing
Systems. Vol 34. Curran Associates; 2021:14873-14886.'
apa: 'Frantar, E., Kurtic, E., & Alistarh, D.-A. (2021). M-FAC: Efficient matrix-free
approximations of second-order information. In 35th Conference on Neural Information
Processing Systems (Vol. 34, pp. 14873–14886). Virtual, Online: Curran Associates.'
chicago: 'Frantar, Elias, Eldar Kurtic, and Dan-Adrian Alistarh. “M-FAC: Efficient
Matrix-Free Approximations of Second-Order Information.” In 35th Conference
on Neural Information Processing Systems, 34:14873–86. Curran Associates,
2021.'
ieee: 'E. Frantar, E. Kurtic, and D.-A. Alistarh, “M-FAC: Efficient matrix-free
approximations of second-order information,” in 35th Conference on Neural Information
Processing Systems, Virtual, Online, 2021, vol. 34, pp. 14873–14886.'
ista: 'Frantar E, Kurtic E, Alistarh D-A. 2021. M-FAC: Efficient matrix-free approximations
of second-order information. 35th Conference on Neural Information Processing
Systems. NeurIPS: Neural Information Processing Systems vol. 34, 14873–14886.'
mla: 'Frantar, Elias, et al. “M-FAC: Efficient Matrix-Free Approximations of Second-Order
Information.” 35th Conference on Neural Information Processing Systems,
vol. 34, Curran Associates, 2021, pp. 14873–86.'
short: E. Frantar, E. Kurtic, D.-A. Alistarh, in:, 35th Conference on Neural Information
Processing Systems, Curran Associates, 2021, pp. 14873–14886.
conference:
end_date: 2021-12-14
location: Virtual, Online
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2021-12-06
date_created: 2022-06-26T22:01:35Z
date_published: 2021-12-06T00:00:00Z
date_updated: 2022-06-27T07:05:12Z
day: '06'
department:
- _id: DaAl
ec_funded: 1
external_id:
arxiv:
- '2010.08222'
intvolume: ' 34'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://proceedings.neurips.cc/paper/2021/file/7cfd5df443b4eb0d69886a583b33de4c-Paper.pdf
month: '12'
oa: 1
oa_version: Published Version
page: 14873-14886
project:
- _id: 268A44D6-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '805223'
name: Elastic Coordination for Scalable Machine Learning
publication: 35th Conference on Neural Information Processing Systems
publication_identifier:
isbn:
- '9781713845393'
issn:
- 1049-5258
publication_status: published
publisher: Curran Associates
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'M-FAC: Efficient matrix-free approximations of second-order information'
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 34
year: '2021'
...
---
_id: '11464'
abstract:
- lang: eng
text: "We consider a standard distributed optimisation setting where N machines,
each holding a d-dimensional function\r\nfi, aim to jointly minimise the sum of
the functions ∑Ni=1fi(x). This problem arises naturally in large-scale distributed
optimisation, where a standard solution is to apply variants of (stochastic) gradient
descent. We focus on the communication complexity of this problem: our main result
provides the first fully unconditional bounds on total number of bits which need
to be sent and received by the N machines to solve this problem under point-to-point
communication, within a given error-tolerance. Specifically, we show that Ω(Ndlogd/Nε)
total bits need to be communicated between the machines to find an additive ϵ-approximation
to the minimum of ∑Ni=1fi(x). The result holds for both deterministic and randomised
algorithms, and, importantly, requires no assumptions on the algorithm structure.
The lower bound is tight under certain restrictions on parameter values, and is
matched within constant factors for quadratic objectives by a new variant of quantised
gradient descent, which we describe and analyse. Our results bring over tools
from communication complexity to distributed optimisation, which has potential
for further applications."
acknowledgement: We thank the NeurIPS reviewers for insightful comments that helped
us improve the positioning of our results, as well as for pointing out the subsampling
approach for complementing the randomised lower bound. We also thank Foivos Alimisis
and Peter Davies for useful discussions. This project has received funding from
the European Research Council (ERC) under the European Union’s Horizon 2020 research
and innovation programme (grant agreement No 805223 ScaleML).
article_processing_charge: No
arxiv: 1
author:
- first_name: Dan-Adrian
full_name: Alistarh, Dan-Adrian
id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
last_name: Alistarh
orcid: 0000-0003-3650-940X
- first_name: Janne
full_name: Korhonen, Janne
id: C5402D42-15BC-11E9-A202-CA2BE6697425
last_name: Korhonen
citation:
ama: 'Alistarh D-A, Korhonen J. Towards tight communication lower bounds for distributed
optimisation. In: 35th Conference on Neural Information Processing Systems.
Vol 34. Curran Associates; 2021:7254-7266.'
apa: 'Alistarh, D.-A., & Korhonen, J. (2021). Towards tight communication lower
bounds for distributed optimisation. In 35th Conference on Neural Information
Processing Systems (Vol. 34, pp. 7254–7266). Virtual, Online: Curran Associates.'
chicago: Alistarh, Dan-Adrian, and Janne Korhonen. “Towards Tight Communication
Lower Bounds for Distributed Optimisation.” In 35th Conference on Neural Information
Processing Systems, 34:7254–66. Curran Associates, 2021.
ieee: D.-A. Alistarh and J. Korhonen, “Towards tight communication lower bounds
for distributed optimisation,” in 35th Conference on Neural Information Processing
Systems, Virtual, Online, 2021, vol. 34, pp. 7254–7266.
ista: 'Alistarh D-A, Korhonen J. 2021. Towards tight communication lower bounds
for distributed optimisation. 35th Conference on Neural Information Processing
Systems. NeurIPS: Neural Information Processing Systems vol. 34, 7254–7266.'
mla: Alistarh, Dan-Adrian, and Janne Korhonen. “Towards Tight Communication Lower
Bounds for Distributed Optimisation.” 35th Conference on Neural Information
Processing Systems, vol. 34, Curran Associates, 2021, pp. 7254–66.
short: D.-A. Alistarh, J. Korhonen, in:, 35th Conference on Neural Information Processing
Systems, Curran Associates, 2021, pp. 7254–7266.
conference:
end_date: 2021-12-14
location: Virtual, Online
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2021-12-06
date_created: 2022-06-26T22:01:35Z
date_published: 2021-12-06T00:00:00Z
date_updated: 2022-06-27T06:54:31Z
day: '06'
department:
- _id: DaAl
ec_funded: 1
external_id:
arxiv:
- '2010.08222'
intvolume: ' 34'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://proceedings.neurips.cc/paper/2021/file/3b92d18aa7a6176dd37d372bc2f1eb71-Paper.pdf
month: '12'
oa: 1
oa_version: Published Version
page: 7254-7266
project:
- _id: 268A44D6-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '805223'
name: Elastic Coordination for Scalable Machine Learning
publication: 35th Conference on Neural Information Processing Systems
publication_identifier:
isbn:
- '9781713845393'
issn:
- 1049-5258
publication_status: published
publisher: Curran Associates
quality_controlled: '1'
scopus_import: '1'
status: public
title: Towards tight communication lower bounds for distributed optimisation
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 34
year: '2021'
...
---
_id: '12076'
abstract:
- lang: eng
text: We find an asymptotic formula for the number of primitive vectors $(z_1,\ldots,z_4)\in
(\mathbb{Z}_{\neq 0})^4$ such that $z_1,\ldots, z_4$ are all squareful and bounded
by $B$, and $z_1+\cdots + z_4 = 0$. Our result agrees in the power of $B$ and
$\log B$ with the Campana-Manin conjecture of Pieropan, Smeets, Tanimoto and V\'{a}rilly-Alvarado.
article_number: '2104.06966'
article_processing_charge: No
arxiv: 1
author:
- first_name: Alec L
full_name: Shute, Alec L
id: 440EB050-F248-11E8-B48F-1D18A9856A87
last_name: Shute
orcid: 0000-0002-1812-2810
citation:
ama: Shute AL. Sums of four squareful numbers. arXiv. doi:10.48550/arXiv.2104.06966
apa: Shute, A. L. (n.d.). Sums of four squareful numbers. arXiv. https://doi.org/10.48550/arXiv.2104.06966
chicago: Shute, Alec L. “Sums of Four Squareful Numbers.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2104.06966.
ieee: A. L. Shute, “Sums of four squareful numbers,” arXiv. .
ista: Shute AL. Sums of four squareful numbers. arXiv, 2104.06966.
mla: Shute, Alec L. “Sums of Four Squareful Numbers.” ArXiv, 2104.06966,
doi:10.48550/arXiv.2104.06966.
short: A.L. Shute, ArXiv (n.d.).
date_created: 2022-09-09T10:42:51Z
date_published: 2021-04-15T00:00:00Z
date_updated: 2023-02-21T16:37:30Z
day: '15'
department:
- _id: TiBr
doi: 10.48550/arXiv.2104.06966
external_id:
arxiv:
- '2104.06966'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2104.06966
month: '04'
oa: 1
oa_version: Preprint
publication: arXiv
publication_status: submitted
related_material:
record:
- id: '12072'
relation: dissertation_contains
status: public
status: public
title: Sums of four squareful numbers
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2021'
...
---
_id: '12077'
abstract:
- lang: eng
text: "We compare the Manin-type conjecture for Campana points recently formulated\r\nby
Pieropan, Smeets, Tanimoto and V\\'{a}rilly-Alvarado with an alternative\r\nprediction
of Browning and Van Valckenborgh in the special case of the orbifold\r\n$(\\mathbb{P}^1,D)$,
where $D =\\frac{1}{2}[0]+\\frac{1}{2}[1]+\\frac{1}{2}[\\infty]$. We find that
the two predicted leading constants do not agree, and we discuss whether thin
sets\r\ncould explain this discrepancy. Motivated by this, we provide a counterexample\r\nto
the Manin-type conjecture for Campana points, by considering orbifolds\r\ncorresponding
to squareful values of binary quadratic forms."
acknowledgement: The author would like to thank Damaris Schindler and Florian Wilsch
for their helpful comments on the heights and Tamagawa measures used in Section
3, together with Marta Pieropan, Sho Tanimoto and Sam Streeter for providing valuable
feedback on an earlier version of this paper, and Tim Browning for many useful comments
and discussions during the development of this work. The author is also grateful
to the anonymous referee for providing many valuable comments and suggestions that
improved the quality of the paper.
article_number: '2104.14946'
article_processing_charge: No
arxiv: 1
author:
- first_name: Alec L
full_name: Shute, Alec L
id: 440EB050-F248-11E8-B48F-1D18A9856A87
last_name: Shute
orcid: 0000-0002-1812-2810
citation:
ama: Shute AL. On the leading constant in the Manin-type conjecture for Campana
points. arXiv. doi:10.48550/arXiv.2104.14946
apa: Shute, A. L. (n.d.). On the leading constant in the Manin-type conjecture for
Campana points. arXiv. https://doi.org/10.48550/arXiv.2104.14946
chicago: Shute, Alec L. “On the Leading Constant in the Manin-Type Conjecture for
Campana Points.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2104.14946.
ieee: A. L. Shute, “On the leading constant in the Manin-type conjecture for Campana
points,” arXiv. .
ista: Shute AL. On the leading constant in the Manin-type conjecture for Campana
points. arXiv, 2104.14946.
mla: Shute, Alec L. “On the Leading Constant in the Manin-Type Conjecture for Campana
Points.” ArXiv, 2104.14946, doi:10.48550/arXiv.2104.14946.
short: A.L. Shute, ArXiv (n.d.).
date_created: 2022-09-09T10:43:17Z
date_published: 2021-04-30T00:00:00Z
date_updated: 2023-02-21T16:37:30Z
day: '30'
department:
- _id: TiBr
doi: 10.48550/arXiv.2104.14946
external_id:
arxiv:
- '2104.14946'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2104.14946
month: '04'
oa: 1
oa_version: Preprint
publication: arXiv
publication_status: submitted
related_material:
record:
- id: '12072'
relation: dissertation_contains
status: public
status: public
title: On the leading constant in the Manin-type conjecture for Campana points
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2021'
...
---
_id: '12188'
abstract:
- lang: eng
text: Molecular mechanisms enabling the switching and maintenance of epigenetic
states are not fully understood. Distinct histone modifications are often associated
with ON/OFF epigenetic states, but how these states are stably maintained through
DNA replication, yet in certain situations switch from one to another remains
unclear. Here, we address this problem through identification of Arabidopsis INCURVATA11
(ICU11) as a Polycomb Repressive Complex 2 accessory protein. ICU11 robustly immunoprecipitated
in vivo with PRC2 core components and the accessory proteins, EMBRYONIC FLOWER
1 (EMF1), LIKE HETEROCHROMATIN PROTEIN1 (LHP1), and TELOMERE_REPEAT_BINDING FACTORS
(TRBs). ICU11 encodes a 2-oxoglutarate-dependent dioxygenase, an activity associated
with histone demethylation in other organisms, and mutant plants show defects
in multiple aspects of the Arabidopsis epigenome. To investigate its primary molecular
function we identified the Arabidopsis FLOWERING LOCUS C (FLC) as a direct target
and found icu11 disrupted the cold-induced, Polycomb-mediated silencing underlying
vernalization. icu11 prevented reduction in H3K36me3 levels normally seen during
the early cold phase, supporting a role for ICU11 in H3K36me3 demethylation. This
was coincident with an attenuation of H3K27me3 at the internal nucleation site
in FLC, and reduction in H3K27me3 levels across the body of the gene after plants
were returned to the warm. Thus, ICU11 is required for the cold-induced epigenetic
switching between the mutually exclusive chromatin states at FLC, from the active
H3K36me3 state to the silenced H3K27me3 state. These data support the importance
of physical coupling of histone modification activities to promote epigenetic
switching between opposing chromatin states.
acknowledgement: We would like to thank Scott Berry for help with ICU-GFP nuclear
localization microscopy, Hao Yu and Lisha Shen for assistance with 6mA DNA methylation
analysis, Donna Gibson for graphic design assistance, and members of the C.D. and
Howard laboratories for helpful discussions. This work was funded by the European
Research Council grants to “MEXTIM” (to C.D.) and “SexMeth” (to X. Feng), by the
Biotechnological and Biological Sciences Research Council (BBSRC) Institute Strategic
Programmes GRO (BB/J004588/1), GEN (BB/P013511/1), BBSRC grant (to X. Feng) (BB/S009620/1),
and the Marie Sklodowska–Curie Postdoctoral Fellowships “UNRAVEL” (to R.H.B.) and
"WISDOM" (to X. Fang). Additional funding via the Wellcome Trust through a Senior
Research Fellowship (to J.R.) (103139) and a multiuser equipment grant (108504).
The Wellcome Centre for Cell Biology is supported by core funding from the Wellcome
Trust (203149).
article_processing_charge: No
article_type: original
author:
- first_name: Rebecca H.
full_name: Bloomer, Rebecca H.
last_name: Bloomer
- first_name: Claire E.
full_name: Hutchison, Claire E.
last_name: Hutchison
- first_name: Isabel
full_name: Bäurle, Isabel
last_name: Bäurle
- first_name: James
full_name: Walker, James
last_name: Walker
- first_name: Xiaofeng
full_name: Fang, Xiaofeng
last_name: Fang
- first_name: Pumi
full_name: Perera, Pumi
last_name: Perera
- first_name: Christos N.
full_name: Velanis, Christos N.
last_name: Velanis
- first_name: Serin
full_name: Gümüs, Serin
last_name: Gümüs
- first_name: Christos
full_name: Spanos, Christos
last_name: Spanos
- first_name: Juri
full_name: Rappsilber, Juri
last_name: Rappsilber
- first_name: Xiaoqi
full_name: Feng, Xiaoqi
id: e0164712-22ee-11ed-b12a-d80fcdf35958
last_name: Feng
orcid: 0000-0002-4008-1234
- first_name: Justin
full_name: Goodrich, Justin
last_name: Goodrich
- first_name: Caroline
full_name: Dean, Caroline
last_name: Dean
citation:
ama: Bloomer RH, Hutchison CE, Bäurle I, et al. The Arabidopsis epigenetic regulator
ICU11 as an accessory protein of polycomb repressive complex 2. Proceedings
of the National Academy of Sciences. 2020;117(28):16660-16666. doi:10.1073/pnas.1920621117
apa: Bloomer, R. H., Hutchison, C. E., Bäurle, I., Walker, J., Fang, X., Perera,
P., … Dean, C. (2020). The Arabidopsis epigenetic regulator ICU11 as an accessory
protein of polycomb repressive complex 2. Proceedings of the National Academy
of Sciences. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1920621117
chicago: Bloomer, Rebecca H., Claire E. Hutchison, Isabel Bäurle, James Walker,
Xiaofeng Fang, Pumi Perera, Christos N. Velanis, et al. “The Arabidopsis Epigenetic
Regulator ICU11 as an Accessory Protein of Polycomb Repressive Complex 2.” Proceedings
of the National Academy of Sciences. Proceedings of the National Academy of
Sciences, 2020. https://doi.org/10.1073/pnas.1920621117.
ieee: R. H. Bloomer et al., “The Arabidopsis epigenetic regulator ICU11
as an accessory protein of polycomb repressive complex 2,” Proceedings of the
National Academy of Sciences, vol. 117, no. 28. Proceedings of the National
Academy of Sciences, pp. 16660–16666, 2020.
ista: Bloomer RH, Hutchison CE, Bäurle I, Walker J, Fang X, Perera P, Velanis CN,
Gümüs S, Spanos C, Rappsilber J, Feng X, Goodrich J, Dean C. 2020. The Arabidopsis
epigenetic regulator ICU11 as an accessory protein of polycomb repressive complex
2. Proceedings of the National Academy of Sciences. 117(28), 16660–16666.
mla: Bloomer, Rebecca H., et al. “The Arabidopsis Epigenetic Regulator ICU11 as
an Accessory Protein of Polycomb Repressive Complex 2.” Proceedings of the
National Academy of Sciences, vol. 117, no. 28, Proceedings of the National
Academy of Sciences, 2020, pp. 16660–66, doi:10.1073/pnas.1920621117.
short: R.H. Bloomer, C.E. Hutchison, I. Bäurle, J. Walker, X. Fang, P. Perera, C.N.
Velanis, S. Gümüs, C. Spanos, J. Rappsilber, X. Feng, J. Goodrich, C. Dean, Proceedings
of the National Academy of Sciences 117 (2020) 16660–16666.
date_created: 2023-01-16T09:15:44Z
date_published: 2020-05-22T00:00:00Z
date_updated: 2023-05-08T10:53:55Z
day: '22'
ddc:
- '580'
department:
- _id: XiFe
doi: 10.1073/pnas.1920621117
extern: '1'
external_id:
pmid:
- '32601198'
file:
- access_level: open_access
checksum: cedee184cb12f454f2fba4158ff47db9
content_type: application/pdf
creator: alisjak
date_created: 2023-02-07T11:29:55Z
date_updated: 2023-02-07T11:29:55Z
file_id: '12526'
file_name: 2020_PNAS_Bloomer.pdf
file_size: 1105414
relation: main_file
success: 1
file_date_updated: 2023-02-07T11:29:55Z
has_accepted_license: '1'
intvolume: ' 117'
issue: '28'
keyword:
- Multidisciplinary
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7368280/
month: '05'
oa: 1
oa_version: Published Version
page: 16660-16666
pmid: 1
publication: Proceedings of the National Academy of Sciences
publication_identifier:
issn:
- 0027-8424
- 1091-6490
publication_status: published
publisher: Proceedings of the National Academy of Sciences
quality_controlled: '1'
scopus_import: '1'
status: public
title: The Arabidopsis epigenetic regulator ICU11 as an accessory protein of polycomb
repressive complex 2
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 117
year: '2020'
...
---
_id: '12189'
abstract:
- lang: eng
text: Meiotic crossovers (COs) are important for reshuffling genetic information
between homologous chromosomes and they are essential for their correct segregation.
COs are unevenly distributed along chromosomes and the underlying mechanisms controlling
CO localization are not well understood. We previously showed that meiotic COs
are mis-localized in the absence of AXR1, an enzyme involved in the neddylation/rubylation
protein modification pathway in Arabidopsis thaliana. Here, we report that in
axr1-/-, male meiocytes show a strong defect in chromosome pairing whereas the
formation of the telomere bouquet is not affected. COs are also redistributed
towards subtelomeric chromosomal ends where they frequently form clusters, in
contrast to large central regions depleted in recombination. The CO suppressed
regions correlate with DNA hypermethylation of transposable elements (TEs) in
the CHH context in axr1-/- meiocytes. Through examining somatic methylomes, we
found axr1-/- affects DNA methylation in a plant, causing hypermethylation in
all sequence contexts (CG, CHG and CHH) in TEs. Impairment of the main pathways
involved in DNA methylation is epistatic over axr1-/- for DNA methylation in somatic
cells but does not restore regular chromosome segregation during meiosis. Collectively,
our findings reveal that the neddylation pathway not only regulates hormonal perception
and CO distribution but is also, directly or indirectly, a major limiting pathway
of TE DNA methylation in somatic cells.
acknowledgement: The authors wish to thank Cécile Raynaud, Eric Jenczewski, Rajeev
Kumar, Raphaël Mercier and Jean Molinier for critical reading of the manuscript.
article_number: e1008894
article_processing_charge: No
article_type: original
author:
- first_name: Nicolas
full_name: Christophorou, Nicolas
last_name: Christophorou
- first_name: Wenjing
full_name: She, Wenjing
last_name: She
- first_name: Jincheng
full_name: Long, Jincheng
last_name: Long
- first_name: Aurélie
full_name: Hurel, Aurélie
last_name: Hurel
- first_name: Sébastien
full_name: Beaubiat, Sébastien
last_name: Beaubiat
- first_name: Yassir
full_name: Idir, Yassir
last_name: Idir
- first_name: Marina
full_name: Tagliaro-Jahns, Marina
last_name: Tagliaro-Jahns
- first_name: Aurélie
full_name: Chambon, Aurélie
last_name: Chambon
- first_name: Victor
full_name: Solier, Victor
last_name: Solier
- first_name: Daniel
full_name: Vezon, Daniel
last_name: Vezon
- first_name: Mathilde
full_name: Grelon, Mathilde
last_name: Grelon
- first_name: Xiaoqi
full_name: Feng, Xiaoqi
id: e0164712-22ee-11ed-b12a-d80fcdf35958
last_name: Feng
orcid: 0000-0002-4008-1234
- first_name: Nicolas
full_name: Bouché, Nicolas
last_name: Bouché
- first_name: Christine
full_name: Mézard, Christine
last_name: Mézard
citation:
ama: Christophorou N, She W, Long J, et al. AXR1 affects DNA methylation independently
of its role in regulating meiotic crossover localization. PLOS Genetics.
2020;16(6). doi:10.1371/journal.pgen.1008894
apa: Christophorou, N., She, W., Long, J., Hurel, A., Beaubiat, S., Idir, Y., …
Mézard, C. (2020). AXR1 affects DNA methylation independently of its role in regulating
meiotic crossover localization. PLOS Genetics. Public Library of Science
(PLoS). https://doi.org/10.1371/journal.pgen.1008894
chicago: Christophorou, Nicolas, Wenjing She, Jincheng Long, Aurélie Hurel, Sébastien
Beaubiat, Yassir Idir, Marina Tagliaro-Jahns, et al. “AXR1 Affects DNA Methylation
Independently of Its Role in Regulating Meiotic Crossover Localization.” PLOS
Genetics. Public Library of Science (PLoS), 2020. https://doi.org/10.1371/journal.pgen.1008894.
ieee: N. Christophorou et al., “AXR1 affects DNA methylation independently
of its role in regulating meiotic crossover localization,” PLOS Genetics,
vol. 16, no. 6. Public Library of Science (PLoS), 2020.
ista: Christophorou N, She W, Long J, Hurel A, Beaubiat S, Idir Y, Tagliaro-Jahns
M, Chambon A, Solier V, Vezon D, Grelon M, Feng X, Bouché N, Mézard C. 2020. AXR1
affects DNA methylation independently of its role in regulating meiotic crossover
localization. PLOS Genetics. 16(6), e1008894.
mla: Christophorou, Nicolas, et al. “AXR1 Affects DNA Methylation Independently
of Its Role in Regulating Meiotic Crossover Localization.” PLOS Genetics,
vol. 16, no. 6, e1008894, Public Library of Science (PLoS), 2020, doi:10.1371/journal.pgen.1008894.
short: N. Christophorou, W. She, J. Long, A. Hurel, S. Beaubiat, Y. Idir, M. Tagliaro-Jahns,
A. Chambon, V. Solier, D. Vezon, M. Grelon, X. Feng, N. Bouché, C. Mézard, PLOS
Genetics 16 (2020).
date_created: 2023-01-16T09:16:10Z
date_published: 2020-06-29T00:00:00Z
date_updated: 2023-05-08T10:54:39Z
day: '29'
department:
- _id: XiFe
doi: 10.1371/journal.pgen.1008894
extern: '1'
external_id:
pmid:
- '32598340'
intvolume: ' 16'
issue: '6'
keyword:
- Cancer Research
- Genetics (clinical)
- Genetics
- Molecular Biology
- Ecology
- Evolution
- Behavior and Systematics
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7351236/
month: '06'
oa: 1
oa_version: Published Version
pmid: 1
publication: PLOS Genetics
publication_identifier:
issn:
- 1553-7404
publication_status: published
publisher: Public Library of Science (PLoS)
quality_controlled: '1'
scopus_import: '1'
status: public
title: AXR1 affects DNA methylation independently of its role in regulating meiotic
crossover localization
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 16
year: '2020'
...
---
_id: '13056'
abstract:
- lang: eng
text: This datasets comprises all data shown in plots of the submitted article "Converting
microwave and telecom photons with a silicon photonic nanomechanical interface".
Additional raw data are available from the corresponding author on reasonable
request.
article_processing_charge: No
author:
- first_name: Georg M
full_name: Arnold, Georg M
id: 3770C838-F248-11E8-B48F-1D18A9856A87
last_name: Arnold
orcid: 0000-0003-1397-7876
- first_name: Matthias
full_name: Wulf, Matthias
id: 45598606-F248-11E8-B48F-1D18A9856A87
last_name: Wulf
orcid: 0000-0001-6613-1378
- first_name: Shabir
full_name: Barzanjeh, Shabir
id: 2D25E1F6-F248-11E8-B48F-1D18A9856A87
last_name: Barzanjeh
orcid: 0000-0003-0415-1423
- first_name: Elena
full_name: Redchenko, Elena
id: 2C21D6E8-F248-11E8-B48F-1D18A9856A87
last_name: Redchenko
- first_name: Alfredo R
full_name: Rueda Sanchez, Alfredo R
id: 3B82B0F8-F248-11E8-B48F-1D18A9856A87
last_name: Rueda Sanchez
orcid: 0000-0001-6249-5860
- first_name: William J
full_name: Hease, William J
id: 29705398-F248-11E8-B48F-1D18A9856A87
last_name: Hease
orcid: 0000-0001-9868-2166
- first_name: Farid
full_name: Hassani, Farid
id: 2AED110C-F248-11E8-B48F-1D18A9856A87
last_name: Hassani
orcid: 0000-0001-6937-5773
- first_name: Johannes M
full_name: Fink, Johannes M
id: 4B591CBA-F248-11E8-B48F-1D18A9856A87
last_name: Fink
orcid: 0000-0001-8112-028X
citation:
ama: Arnold GM, Wulf M, Barzanjeh S, et al. Converting microwave and telecom photons
with a silicon photonic nanomechanical interface. 2020. doi:10.5281/ZENODO.3961561
apa: Arnold, G. M., Wulf, M., Barzanjeh, S., Redchenko, E., Rueda Sanchez, A. R.,
Hease, W. J., … Fink, J. M. (2020). Converting microwave and telecom photons with
a silicon photonic nanomechanical interface. Zenodo. https://doi.org/10.5281/ZENODO.3961561
chicago: Arnold, Georg M, Matthias Wulf, Shabir Barzanjeh, Elena Redchenko, Alfredo
R Rueda Sanchez, William J Hease, Farid Hassani, and Johannes M Fink. “Converting
Microwave and Telecom Photons with a Silicon Photonic Nanomechanical Interface.”
Zenodo, 2020. https://doi.org/10.5281/ZENODO.3961561.
ieee: G. M. Arnold et al., “Converting microwave and telecom photons with
a silicon photonic nanomechanical interface.” Zenodo, 2020.
ista: Arnold GM, Wulf M, Barzanjeh S, Redchenko E, Rueda Sanchez AR, Hease WJ, Hassani
F, Fink JM. 2020. Converting microwave and telecom photons with a silicon photonic
nanomechanical interface, Zenodo, 10.5281/ZENODO.3961561.
mla: Arnold, Georg M., et al. Converting Microwave and Telecom Photons with a
Silicon Photonic Nanomechanical Interface. Zenodo, 2020, doi:10.5281/ZENODO.3961561.
short: G.M. Arnold, M. Wulf, S. Barzanjeh, E. Redchenko, A.R. Rueda Sanchez, W.J.
Hease, F. Hassani, J.M. Fink, (2020).
date_created: 2023-05-23T13:37:41Z
date_published: 2020-07-27T00:00:00Z
date_updated: 2024-09-10T12:23:51Z
day: '27'
ddc:
- '530'
department:
- _id: JoFi
doi: 10.5281/ZENODO.3961561
main_file_link:
- open_access: '1'
url: https://doi.org/10.5281/zenodo.3961562
month: '07'
oa: 1
oa_version: Published Version
publisher: Zenodo
related_material:
record:
- id: '8529'
relation: used_in_publication
status: public
status: public
title: Converting microwave and telecom photons with a silicon photonic nanomechanical
interface
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: research_data_reference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2020'
...
---
_id: '13060'
abstract:
- lang: eng
text: Coinfections with multiple pathogens can result in complex within-host dynamics
affecting virulence and transmission. Whilst multiple infections are intensively
studied in solitary hosts, it is so far unresolved how social host interactions
interfere with pathogen competition, and if this depends on coinfection diversity.
We studied how the collective disease defenses of ants – their social immunity
– influence pathogen competition in coinfections of same or different fungal
pathogen species. Social immunity reduced virulence for all pathogen combinations,
but interfered with spore production only in different-species coinfections. Here,
it decreased overall pathogen sporulation success, whilst simultaneously increasing
co-sporulation on individual cadavers and maintaining a higher pathogen diversity
at the community-level. Mathematical modeling revealed that host sanitary care
alone can modulate competitive outcomes between pathogens, giving advantage to
fast-germinating, thus less grooming-sensitive ones. Host social interactions
can hence modulate infection dynamics in coinfected group members, thereby altering
pathogen communities at the host- and population-level.
article_processing_charge: No
author:
- first_name: Barbara
full_name: Milutinovic, Barbara
id: 2CDC32B8-F248-11E8-B48F-1D18A9856A87
last_name: Milutinovic
orcid: 0000-0002-8214-4758
- first_name: Miriam
full_name: Stock, Miriam
id: 42462816-F248-11E8-B48F-1D18A9856A87
last_name: Stock
- first_name: Anna V
full_name: Grasse, Anna V
id: 406F989C-F248-11E8-B48F-1D18A9856A87
last_name: Grasse
- first_name: Elisabeth
full_name: Naderlinger, Elisabeth
id: 31757262-F248-11E8-B48F-1D18A9856A87
last_name: Naderlinger
- first_name: Christian
full_name: Hilbe, Christian
id: 2FDF8F3C-F248-11E8-B48F-1D18A9856A87
last_name: Hilbe
orcid: 0000-0001-5116-955X
- first_name: Sylvia
full_name: Cremer, Sylvia
id: 2F64EC8C-F248-11E8-B48F-1D18A9856A87
last_name: Cremer
orcid: 0000-0002-2193-3868
citation:
ama: Milutinovic B, Stock M, Grasse AV, Naderlinger E, Hilbe C, Cremer S. Social
immunity modulates competition between coinfecting pathogens. 2020. doi:10.5061/DRYAD.CRJDFN318
apa: Milutinovic, B., Stock, M., Grasse, A. V., Naderlinger, E., Hilbe, C., &
Cremer, S. (2020). Social immunity modulates competition between coinfecting pathogens.
Dryad. https://doi.org/10.5061/DRYAD.CRJDFN318
chicago: Milutinovic, Barbara, Miriam Stock, Anna V Grasse, Elisabeth Naderlinger,
Christian Hilbe, and Sylvia Cremer. “Social Immunity Modulates Competition between
Coinfecting Pathogens.” Dryad, 2020. https://doi.org/10.5061/DRYAD.CRJDFN318.
ieee: B. Milutinovic, M. Stock, A. V. Grasse, E. Naderlinger, C. Hilbe, and S. Cremer,
“Social immunity modulates competition between coinfecting pathogens.” Dryad,
2020.
ista: Milutinovic B, Stock M, Grasse AV, Naderlinger E, Hilbe C, Cremer S. 2020.
Social immunity modulates competition between coinfecting pathogens, Dryad, 10.5061/DRYAD.CRJDFN318.
mla: Milutinovic, Barbara, et al. Social Immunity Modulates Competition between
Coinfecting Pathogens. Dryad, 2020, doi:10.5061/DRYAD.CRJDFN318.
short: B. Milutinovic, M. Stock, A.V. Grasse, E. Naderlinger, C. Hilbe, S. Cremer,
(2020).
date_created: 2023-05-23T16:11:22Z
date_published: 2020-12-19T00:00:00Z
date_updated: 2023-09-05T16:04:48Z
day: '19'
ddc:
- '570'
department:
- _id: SyCr
- _id: KrCh
doi: 10.5061/DRYAD.CRJDFN318
license: https://creativecommons.org/publicdomain/zero/1.0/
main_file_link:
- open_access: '1'
url: https://doi.org/10.5061/dryad.crjdfn318
month: '12'
oa: 1
oa_version: Published Version
publisher: Dryad
related_material:
record:
- id: '7343'
relation: used_in_publication
status: public
status: public
title: Social immunity modulates competition between coinfecting pathogens
tmp:
image: /images/cc_0.png
legal_code_url: https://creativecommons.org/publicdomain/zero/1.0/legalcode
name: Creative Commons Public Domain Dedication (CC0 1.0)
short: CC0 (1.0)
type: research_data_reference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2020'
...
---
_id: '13065'
abstract:
- lang: eng
text: Domestication is a human-induced selection process that imprints the genomes
of domesticated populations over a short evolutionary time scale, and that occurs
in a given demographic context. Reconstructing historical gene flow, effective
population size changes and their timing is therefore of fundamental interest
to understand how plant demography and human selection jointly shape genomic divergence
during domestication. Yet, the comparison under a single statistical framework
of independent domestication histories across different crop species has been
little evaluated so far. Thus, it is unclear whether domestication leads to convergent
demographic changes that similarly affect crop genomes. To address this question,
we used existing and new transcriptome data on three crop species of Solanaceae
(eggplant, pepper and tomato), together with their close wild relatives. We fitted
twelve demographic models of increasing complexity on the unfolded joint allele
frequency spectrum for each wild/crop pair, and we found evidence for both shared
and species-specific demographic processes between species. A convergent history
of domestication with gene-flow was inferred for all three species, along with
evidence of strong reduction in the effective population size during the cultivation
stage of tomato and pepper. The absence of any reduction in size of the crop in
eggplant stands out from the classical view of the domestication process; as does
the existence of a “protracted period” of management before cultivation. Our results
also suggest divergent management strategies of modern cultivars among species
as their current demography substantially differs. Finally, the timing of domestication
is species-specific and supported by the few historical records available.
article_processing_charge: No
author:
- first_name: Stephanie
full_name: Arnoux, Stephanie
last_name: Arnoux
- first_name: Christelle
full_name: Fraisse, Christelle
id: 32DF5794-F248-11E8-B48F-1D18A9856A87
last_name: Fraisse
orcid: 0000-0001-8441-5075
- first_name: Christopher
full_name: Sauvage, Christopher
last_name: Sauvage
citation:
ama: 'Arnoux S, Fraisse C, Sauvage C. VCF files of synonymous SNPs related to: Genomic
inference of complex domestication histories in three Solanaceae species. 2020.
doi:10.5061/DRYAD.Q2BVQ83HD'
apa: 'Arnoux, S., Fraisse, C., & Sauvage, C. (2020). VCF files of synonymous
SNPs related to: Genomic inference of complex domestication histories in three
Solanaceae species. Dryad. https://doi.org/10.5061/DRYAD.Q2BVQ83HD'
chicago: 'Arnoux, Stephanie, Christelle Fraisse, and Christopher Sauvage. “VCF Files
of Synonymous SNPs Related to: Genomic Inference of Complex Domestication Histories
in Three Solanaceae Species.” Dryad, 2020. https://doi.org/10.5061/DRYAD.Q2BVQ83HD.'
ieee: 'S. Arnoux, C. Fraisse, and C. Sauvage, “VCF files of synonymous SNPs related
to: Genomic inference of complex domestication histories in three Solanaceae species.”
Dryad, 2020.'
ista: 'Arnoux S, Fraisse C, Sauvage C. 2020. VCF files of synonymous SNPs related
to: Genomic inference of complex domestication histories in three Solanaceae species,
Dryad, 10.5061/DRYAD.Q2BVQ83HD.'
mla: 'Arnoux, Stephanie, et al. VCF Files of Synonymous SNPs Related to: Genomic
Inference of Complex Domestication Histories in Three Solanaceae Species.
Dryad, 2020, doi:10.5061/DRYAD.Q2BVQ83HD.'
short: S. Arnoux, C. Fraisse, C. Sauvage, (2020).
date_created: 2023-05-23T16:30:20Z
date_published: 2020-10-19T00:00:00Z
date_updated: 2023-08-04T11:19:26Z
day: '19'
ddc:
- '570'
department:
- _id: NiBa
doi: 10.5061/DRYAD.Q2BVQ83HD
main_file_link:
- open_access: '1'
url: https://doi.org/10.5061/dryad.q2bvq83hd
month: '10'
oa: 1
oa_version: Published Version
publisher: Dryad
related_material:
link:
- relation: software
url: https://github.com/starnoux/arnoux_et_al_2019
record:
- id: '8928'
relation: used_in_publication
status: public
status: public
title: 'VCF files of synonymous SNPs related to: Genomic inference of complex domestication
histories in three Solanaceae species'
tmp:
image: /images/cc_0.png
legal_code_url: https://creativecommons.org/publicdomain/zero/1.0/legalcode
name: Creative Commons Public Domain Dedication (CC0 1.0)
short: CC0 (1.0)
type: research_data_reference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2020'
...