---
_id: '12508'
abstract:
- lang: eng
  text: "We explore the notion of history-determinism in the context of timed automata
    (TA). History-deterministic automata are those in which nondeterminism can be
    resolved on the fly, based on the run constructed thus far. History-determinism
    is a robust property that admits different game-based characterisations, and history-deterministic
    specifications allow for game-based verification without an expensive determinization
    step.\r\nWe show yet another characterisation of history-determinism in terms
    of fair simulation, at the general level of labelled transition systems: a system
    is history-deterministic precisely if and only if it fairly simulates all language
    smaller systems.\r\nFor timed automata over infinite timed words it is known that
    universality is undecidable for Büchi TA. We show that for history-deterministic
    TA with arbitrary parity acceptance, timed universality, inclusion, and synthesis
    all remain decidable and are ExpTime-complete.\r\nFor the subclass of TA with
    safety or reachability acceptance, we show that checking whether such an automaton
    is history-deterministic is decidable (in ExpTime), and history-deterministic
    TA with safety acceptance are effectively determinizable without introducing new
    automata states."
acknowledgement: "Thomas A. Henzinger: This work was supported in part by the ERC-2020-AdG
  101020093.\r\nPatrick Totzke: acknowledges support from the EPSRC, project no. EP/V025848/1.\r\n"
alternative_title:
- LIPIcs
article_processing_charge: No
author:
- first_name: Thomas A
  full_name: Henzinger, Thomas A
  id: 40876CD8-F248-11E8-B48F-1D18A9856A87
  last_name: Henzinger
  orcid: 0000-0002-2985-7724
- first_name: Karoliina
  full_name: Lehtinen, Karoliina
  last_name: Lehtinen
- first_name: Patrick
  full_name: Totzke, Patrick
  last_name: Totzke
citation:
  ama: 'Henzinger TA, Lehtinen K, Totzke P. History-deterministic timed automata.
    In: <i>33rd International Conference on Concurrency Theory</i>. Vol 243. Schloss
    Dagstuhl - Leibniz-Zentrum für Informatik; 2022:14:1-14:21. doi:<a href="https://doi.org/10.4230/LIPIcs.CONCUR.2022.14">10.4230/LIPIcs.CONCUR.2022.14</a>'
  apa: 'Henzinger, T. A., Lehtinen, K., &#38; Totzke, P. (2022). History-deterministic
    timed automata. In <i>33rd International Conference on Concurrency Theory</i>
    (Vol. 243, p. 14:1-14:21). Warsaw, Poland: Schloss Dagstuhl - Leibniz-Zentrum
    für Informatik. <a href="https://doi.org/10.4230/LIPIcs.CONCUR.2022.14">https://doi.org/10.4230/LIPIcs.CONCUR.2022.14</a>'
  chicago: Henzinger, Thomas A, Karoliina Lehtinen, and Patrick Totzke. “History-Deterministic
    Timed Automata.” In <i>33rd International Conference on Concurrency Theory</i>,
    243:14:1-14:21. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022. <a href="https://doi.org/10.4230/LIPIcs.CONCUR.2022.14">https://doi.org/10.4230/LIPIcs.CONCUR.2022.14</a>.
  ieee: T. A. Henzinger, K. Lehtinen, and P. Totzke, “History-deterministic timed
    automata,” in <i>33rd International Conference on Concurrency Theory</i>, Warsaw,
    Poland, 2022, vol. 243, p. 14:1-14:21.
  ista: 'Henzinger TA, Lehtinen K, Totzke P. 2022. History-deterministic timed automata.
    33rd International Conference on Concurrency Theory. CONCUR: Conference on Concurrency
    Theory, LIPIcs, vol. 243, 14:1-14:21.'
  mla: Henzinger, Thomas A., et al. “History-Deterministic Timed Automata.” <i>33rd
    International Conference on Concurrency Theory</i>, vol. 243, Schloss Dagstuhl
    - Leibniz-Zentrum für Informatik, 2022, p. 14:1-14:21, doi:<a href="https://doi.org/10.4230/LIPIcs.CONCUR.2022.14">10.4230/LIPIcs.CONCUR.2022.14</a>.
  short: T.A. Henzinger, K. Lehtinen, P. Totzke, in:, 33rd International Conference
    on Concurrency Theory, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022,
    p. 14:1-14:21.
conference:
  end_date: 2022-09-16
  location: Warsaw, Poland
  name: 'CONCUR: Conference on Concurrency Theory'
  start_date: 2022-09-13
date_created: 2023-02-05T17:24:23Z
date_published: 2022-09-06T00:00:00Z
date_updated: 2023-02-06T09:23:31Z
day: '06'
ddc:
- '000'
department:
- _id: ToHe
doi: 10.4230/LIPIcs.CONCUR.2022.14
ec_funded: 1
file:
- access_level: open_access
  checksum: 9e97e15628f66b2ad77f535bb0327dee
  content_type: application/pdf
  creator: dernst
  date_created: 2023-02-06T09:21:09Z
  date_updated: 2023-02-06T09:21:09Z
  file_id: '12520'
  file_name: 2022_LIPICs_Henzinger2.pdf
  file_size: 717940
  relation: main_file
  success: 1
file_date_updated: 2023-02-06T09:21:09Z
has_accepted_license: '1'
intvolume: '       243'
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
page: 14:1-14:21
project:
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
  call_identifier: H2020
  grant_number: '101020093'
  name: Vigilant Algorithmic Monitoring of Software
publication: 33rd International Conference on Concurrency Theory
publication_identifier:
  isbn:
  - '9783959772464'
  issn:
  - 1868-8969
publication_status: published
publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik
quality_controlled: '1'
scopus_import: '1'
status: public
title: History-deterministic timed automata
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: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 243
year: '2022'
...
---
_id: '12509'
abstract:
- lang: eng
  text: A graph game is a two-player zero-sum game in which the players move a token
    throughout a graph to produce an infinite path, which determines the winner or
    payoff of the game. In bidding games, both players have budgets, and in each turn,
    we hold an "auction" (bidding) to determine which player moves the token. In this
    survey, we consider several bidding mechanisms and their effect on the properties
    of the game. Specifically, bidding games, and in particular bidding games of infinite
    duration, have an intriguing equivalence with random-turn games in which in each
    turn, the player who moves is chosen randomly. We summarize how minor changes
    in the bidding mechanism lead to unexpected differences in the equivalence with
    random-turn games.
acknowledgement: "Guy Avni: Work partially supported by the Israel Science Foundation,
  ISF grant agreement\r\nno 1679/21.\r\nThomas A. Henzinger: This work was supported
  in part by the ERC-2020-AdG 101020093.\r\nWe would like to thank all our collaborators
  Milad Aghajohari, Ventsislav Chonev, Rasmus Ibsen-Jensen, Ismäel Jecker, Petr Novotný,
  Josef Tkadlec, and Ðorđe Žikelić; we hope the collaboration was as fun and meaningful
  for you as it was for us."
article_processing_charge: No
author:
- first_name: Guy
  full_name: Avni, Guy
  id: 463C8BC2-F248-11E8-B48F-1D18A9856A87
  last_name: Avni
  orcid: 0000-0001-5588-8287
- first_name: Thomas A
  full_name: Henzinger, Thomas A
  id: 40876CD8-F248-11E8-B48F-1D18A9856A87
  last_name: Henzinger
  orcid: 0000-0002-2985-7724
citation:
  ama: 'Avni G, Henzinger TA. An updated survey of bidding games on graphs. In: <i>47th
    International Symposium on Mathematical Foundations of Computer Science</i>. Vol
    241. Leibniz International Proceedings in Informatics (LIPIcs). Dagstuhl, Germany:
    Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2022:3:1-3:6. doi:<a href="https://doi.org/10.4230/LIPIcs.MFCS.2022.3">10.4230/LIPIcs.MFCS.2022.3</a>'
  apa: 'Avni, G., &#38; Henzinger, T. A. (2022). An updated survey of bidding games
    on graphs. In <i>47th International Symposium on Mathematical Foundations of Computer
    Science</i> (Vol. 241, p. 3:1-3:6). Dagstuhl, Germany: Schloss Dagstuhl - Leibniz-Zentrum
    für Informatik. <a href="https://doi.org/10.4230/LIPIcs.MFCS.2022.3">https://doi.org/10.4230/LIPIcs.MFCS.2022.3</a>'
  chicago: 'Avni, Guy, and Thomas A Henzinger. “An Updated Survey of Bidding Games
    on Graphs.” In <i>47th International Symposium on Mathematical Foundations of
    Computer Science</i>, 241:3:1-3:6. Leibniz International Proceedings in Informatics
    (LIPIcs). Dagstuhl, Germany: Schloss Dagstuhl - Leibniz-Zentrum für Informatik,
    2022. <a href="https://doi.org/10.4230/LIPIcs.MFCS.2022.3">https://doi.org/10.4230/LIPIcs.MFCS.2022.3</a>.'
  ieee: G. Avni and T. A. Henzinger, “An updated survey of bidding games on graphs,”
    in <i>47th International Symposium on Mathematical Foundations of Computer Science</i>,
    Vienna, Austria, 2022, vol. 241, p. 3:1-3:6.
  ista: 'Avni G, Henzinger TA. 2022. An updated survey of bidding games on graphs.
    47th International Symposium on Mathematical Foundations of Computer Science.
    MFCS: Symposium on Mathematical Foundations of Computer ScienceLeibniz International
    Proceedings in Informatics (LIPIcs) vol. 241, 3:1-3:6.'
  mla: Avni, Guy, and Thomas A. Henzinger. “An Updated Survey of Bidding Games on
    Graphs.” <i>47th International Symposium on Mathematical Foundations of Computer
    Science</i>, vol. 241, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022,
    p. 3:1-3:6, doi:<a href="https://doi.org/10.4230/LIPIcs.MFCS.2022.3">10.4230/LIPIcs.MFCS.2022.3</a>.
  short: G. Avni, T.A. Henzinger, in:, 47th International Symposium on Mathematical
    Foundations of Computer Science, Schloss Dagstuhl - Leibniz-Zentrum für Informatik,
    Dagstuhl, Germany, 2022, p. 3:1-3:6.
conference:
  end_date: 2022-08-26
  location: Vienna, Austria
  name: 'MFCS: Symposium on Mathematical Foundations of Computer Science'
  start_date: 2022-08-22
date_created: 2023-02-05T17:26:01Z
date_published: 2022-08-22T00:00:00Z
date_updated: 2023-02-06T09:16:54Z
day: '22'
ddc:
- '000'
department:
- _id: ToHe
doi: 10.4230/LIPIcs.MFCS.2022.3
ec_funded: 1
file:
- access_level: open_access
  checksum: 1888ec9421622f9526fbec2de035f132
  content_type: application/pdf
  creator: dernst
  date_created: 2023-02-06T09:13:04Z
  date_updated: 2023-02-06T09:13:04Z
  file_id: '12519'
  file_name: 2022_LIPICs_Avni.pdf
  file_size: 624586
  relation: main_file
  success: 1
file_date_updated: 2023-02-06T09:13:04Z
has_accepted_license: '1'
intvolume: '       241'
language:
- iso: eng
month: '08'
oa: 1
oa_version: Published Version
page: 3:1-3:6
place: Dagstuhl, Germany
project:
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
  call_identifier: H2020
  grant_number: '101020093'
  name: Vigilant Algorithmic Monitoring of Software
publication: 47th International Symposium on Mathematical Foundations of Computer
  Science
publication_identifier:
  isbn:
  - '9783959772563'
  issn:
  - 1868-8969
publication_status: published
publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik
quality_controlled: '1'
scopus_import: '1'
series_title: Leibniz International Proceedings in Informatics (LIPIcs)
status: public
title: An updated survey of bidding games on graphs
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: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 241
year: '2022'
...
---
_id: '12510'
abstract:
- lang: eng
  text: "We introduce a new statistical verification algorithm that formally quantifies
    the behavioral robustness of any time-continuous process formulated as a continuous-depth
    model. Our algorithm solves a set of global optimization (Go) problems over a
    given time horizon to construct a tight enclosure (Tube) of the set of all process
    executions starting from a ball of initial states. We call our algorithm GoTube.
    Through its construction, GoTube ensures that the bounding tube is conservative
    up to a desired probability and up to a desired tightness.\r\n GoTube is implemented
    in JAX and optimized to scale to complex continuous-depth neural network models.
    Compared to advanced reachability analysis tools for time-continuous neural networks,
    GoTube does not accumulate overapproximation errors between time steps and avoids
    the infamous wrapping effect inherent in symbolic techniques. We show that GoTube
    substantially outperforms state-of-the-art verification tools in terms of the
    size of the initial ball, speed, time-horizon, task completion, and scalability
    on a large set of experiments.\r\n GoTube is stable and sets the state-of-the-art
    in terms of its ability to scale to time horizons well beyond what has been previously
    possible."
acknowledgement: SG is funded by the Austrian Science Fund (FWF) project number W1255-N23.
  ML and TH are supported in part by FWF under grant Z211-N23 (Wittgenstein Award)
  and the ERC-2020-AdG 101020093. SS is supported by NSF awards DCL-2040599, CCF-1918225,
  and CPS-1446832. RH and DR are partially supported by Boeing. RG is partially supported
  by Horizon-2020 ECSEL Project grant No. 783163 (iDev40).
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Sophie A.
  full_name: Gruenbacher, Sophie A.
  last_name: Gruenbacher
- first_name: Mathias
  full_name: Lechner, Mathias
  id: 3DC22916-F248-11E8-B48F-1D18A9856A87
  last_name: Lechner
- first_name: Ramin
  full_name: Hasani, Ramin
  last_name: Hasani
- first_name: Daniela
  full_name: Rus, Daniela
  last_name: Rus
- first_name: Thomas A
  full_name: Henzinger, Thomas A
  id: 40876CD8-F248-11E8-B48F-1D18A9856A87
  last_name: Henzinger
  orcid: 0000-0002-2985-7724
- first_name: Scott A.
  full_name: Smolka, Scott A.
  last_name: Smolka
- first_name: Radu
  full_name: Grosu, Radu
  last_name: Grosu
citation:
  ama: 'Gruenbacher SA, Lechner M, Hasani R, et al. GoTube: Scalable statistical verification
    of continuous-depth models. <i>Proceedings of the AAAI Conference on Artificial
    Intelligence</i>. 2022;36(6):6755-6764. doi:<a href="https://doi.org/10.1609/aaai.v36i6.20631">10.1609/aaai.v36i6.20631</a>'
  apa: 'Gruenbacher, S. A., Lechner, M., Hasani, R., Rus, D., Henzinger, T. A., Smolka,
    S. A., &#38; Grosu, R. (2022). GoTube: Scalable statistical verification of continuous-depth
    models. <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>.
    Association for the Advancement of Artificial Intelligence. <a href="https://doi.org/10.1609/aaai.v36i6.20631">https://doi.org/10.1609/aaai.v36i6.20631</a>'
  chicago: 'Gruenbacher, Sophie A., Mathias Lechner, Ramin Hasani, Daniela Rus, Thomas
    A Henzinger, Scott A. Smolka, and Radu Grosu. “GoTube: Scalable Statistical Verification
    of Continuous-Depth Models.” <i>Proceedings of the AAAI Conference on Artificial
    Intelligence</i>. Association for the Advancement of Artificial Intelligence,
    2022. <a href="https://doi.org/10.1609/aaai.v36i6.20631">https://doi.org/10.1609/aaai.v36i6.20631</a>.'
  ieee: 'S. A. Gruenbacher <i>et al.</i>, “GoTube: Scalable statistical verification
    of continuous-depth models,” <i>Proceedings of the AAAI Conference on Artificial
    Intelligence</i>, vol. 36, no. 6. Association for the Advancement of Artificial
    Intelligence, pp. 6755–6764, 2022.'
  ista: 'Gruenbacher SA, Lechner M, Hasani R, Rus D, Henzinger TA, Smolka SA, Grosu
    R. 2022. GoTube: Scalable statistical verification of continuous-depth models.
    Proceedings of the AAAI Conference on Artificial Intelligence. 36(6), 6755–6764.'
  mla: 'Gruenbacher, Sophie A., et al. “GoTube: Scalable Statistical Verification
    of Continuous-Depth Models.” <i>Proceedings of the AAAI Conference on Artificial
    Intelligence</i>, vol. 36, no. 6, Association for the Advancement of Artificial
    Intelligence, 2022, pp. 6755–64, doi:<a href="https://doi.org/10.1609/aaai.v36i6.20631">10.1609/aaai.v36i6.20631</a>.'
  short: S.A. Gruenbacher, M. Lechner, R. Hasani, D. Rus, T.A. Henzinger, S.A. Smolka,
    R. Grosu, Proceedings of the AAAI Conference on Artificial Intelligence 36 (2022)
    6755–6764.
date_created: 2023-02-05T17:27:42Z
date_published: 2022-06-28T00:00:00Z
date_updated: 2023-09-26T10:46:59Z
day: '28'
department:
- _id: ToHe
doi: 10.1609/aaai.v36i6.20631
ec_funded: 1
external_id:
  arxiv:
  - '2107.08467'
intvolume: '        36'
issue: '6'
keyword:
- General Medicine
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://arxiv.org/abs/2107.08467
month: '06'
oa: 1
oa_version: Preprint
page: 6755-6764
project:
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
  call_identifier: FWF
  grant_number: Z211
  name: The Wittgenstein Prize
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
  call_identifier: H2020
  grant_number: '101020093'
  name: Vigilant Algorithmic Monitoring of Software
publication: Proceedings of the AAAI Conference on Artificial Intelligence
publication_identifier:
  eissn:
  - 2374-3468
  isbn:
  - '978577358350'
  issn:
  - 2159-5399
publication_status: published
publisher: Association for the Advancement of Artificial Intelligence
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'GoTube: Scalable statistical verification of continuous-depth models'
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 36
year: '2022'
...
---
_id: '12511'
abstract:
- lang: eng
  text: "We consider the problem of formally verifying almost-sure (a.s.) asymptotic
    stability in discrete-time nonlinear stochastic control systems. While verifying
    stability in deterministic control systems is extensively studied in the literature,
    verifying stability in stochastic control systems is an open problem. The few
    existing works on this topic either consider only specialized forms of stochasticity
    or make restrictive assumptions on the system, rendering them inapplicable to
    learning algorithms with neural network policies. \r\n In this work, we present
    an approach for general nonlinear stochastic control problems with two novel aspects:
    (a) instead of classical stochastic extensions of Lyapunov functions, we use ranking
    supermartingales (RSMs) to certify a.s. asymptotic stability, and (b) we present
    a method for learning neural network RSMs. \r\n We prove that our approach guarantees
    a.s. asymptotic stability of the system and\r\n provides the first method to obtain
    bounds on the stabilization time, which stochastic Lyapunov functions do not.\r\n
    Finally, we validate our approach experimentally on a set of nonlinear stochastic
    reinforcement learning environments with neural network policies."
acknowledgement: "This work was supported in part by the ERC-2020-AdG 101020093, ERC
  CoG 863818 (FoRM-SMArt) and the European Union’s Horizon 2020 research and innovation
  programme\r\nunder the Marie Skłodowska-Curie Grant Agreement No. 665385."
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Mathias
  full_name: Lechner, Mathias
  id: 3DC22916-F248-11E8-B48F-1D18A9856A87
  last_name: Lechner
- first_name: Dorde
  full_name: Zikelic, Dorde
  id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
  last_name: Zikelic
  orcid: 0000-0002-4681-1699
- first_name: Krishnendu
  full_name: Chatterjee, Krishnendu
  id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
  last_name: Chatterjee
  orcid: 0000-0002-4561-241X
- first_name: Thomas A
  full_name: Henzinger, Thomas A
  id: 40876CD8-F248-11E8-B48F-1D18A9856A87
  last_name: Henzinger
  orcid: 0000-0002-2985-7724
citation:
  ama: Lechner M, Zikelic D, Chatterjee K, Henzinger TA. Stability verification in
    stochastic control systems via neural network supermartingales. <i>Proceedings
    of the AAAI Conference on Artificial Intelligence</i>. 2022;36(7):7326-7336. doi:<a
    href="https://doi.org/10.1609/aaai.v36i7.20695">10.1609/aaai.v36i7.20695</a>
  apa: Lechner, M., Zikelic, D., Chatterjee, K., &#38; Henzinger, T. A. (2022). Stability
    verification in stochastic control systems via neural network supermartingales.
    <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>. Association
    for the Advancement of Artificial Intelligence. <a href="https://doi.org/10.1609/aaai.v36i7.20695">https://doi.org/10.1609/aaai.v36i7.20695</a>
  chicago: Lechner, Mathias, Dorde Zikelic, Krishnendu Chatterjee, and Thomas A Henzinger.
    “Stability Verification in Stochastic Control Systems via Neural Network Supermartingales.”
    <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>. Association
    for the Advancement of Artificial Intelligence, 2022. <a href="https://doi.org/10.1609/aaai.v36i7.20695">https://doi.org/10.1609/aaai.v36i7.20695</a>.
  ieee: M. Lechner, D. Zikelic, K. Chatterjee, and T. A. Henzinger, “Stability verification
    in stochastic control systems via neural network supermartingales,” <i>Proceedings
    of the AAAI Conference on Artificial Intelligence</i>, vol. 36, no. 7. Association
    for the Advancement of Artificial Intelligence, pp. 7326–7336, 2022.
  ista: Lechner M, Zikelic D, Chatterjee K, Henzinger TA. 2022. Stability verification
    in stochastic control systems via neural network supermartingales. Proceedings
    of the AAAI Conference on Artificial Intelligence. 36(7), 7326–7336.
  mla: Lechner, Mathias, et al. “Stability Verification in Stochastic Control Systems
    via Neural Network Supermartingales.” <i>Proceedings of the AAAI Conference on
    Artificial Intelligence</i>, vol. 36, no. 7, Association for the Advancement of
    Artificial Intelligence, 2022, pp. 7326–36, doi:<a href="https://doi.org/10.1609/aaai.v36i7.20695">10.1609/aaai.v36i7.20695</a>.
  short: M. Lechner, D. Zikelic, K. Chatterjee, T.A. Henzinger, Proceedings of the
    AAAI Conference on Artificial Intelligence 36 (2022) 7326–7336.
date_created: 2023-02-05T17:29:50Z
date_published: 2022-06-28T00:00:00Z
date_updated: 2025-07-14T09:09:58Z
day: '28'
department:
- _id: ToHe
- _id: KrCh
doi: 10.1609/aaai.v36i7.20695
ec_funded: 1
external_id:
  arxiv:
  - '2112.09495'
intvolume: '        36'
issue: '7'
keyword:
- General Medicine
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://arxiv.org/abs/2112.09495
month: '06'
oa: 1
oa_version: Preprint
page: 7326-7336
project:
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
  call_identifier: H2020
  grant_number: '101020093'
  name: Vigilant Algorithmic Monitoring of Software
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
  call_identifier: H2020
  grant_number: '863818'
  name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '665385'
  name: International IST Doctoral Program
publication: Proceedings of the AAAI Conference on Artificial Intelligence
publication_identifier:
  eissn:
  - 2374-3468
  isbn:
  - '9781577358350'
  issn:
  - 2159-5399
publication_status: published
publisher: Association for the Advancement of Artificial Intelligence
quality_controlled: '1'
related_material:
  record:
  - id: '14539'
    relation: dissertation_contains
    status: public
scopus_import: '1'
status: public
title: Stability verification in stochastic control systems via neural network supermartingales
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 36
year: '2022'
...
---
_id: '12516'
abstract:
- lang: eng
  text: "The homogeneous continuous LWE (hCLWE) problem is to distinguish samples
    of a specific high-dimensional Gaussian mixture from standard normal samples.
    It was shown to be at least as hard as Learning with Errors, but no reduction
    in the other direction is currently known.\r\nWe present four new public-key encryption
    schemes based on the hardness of hCLWE, with varying tradeoffs between decryption
    and security errors, and different discretization techniques. Our schemes yield
    a polynomial-time algorithm for solving hCLWE using a Statistical Zero-Knowledge
    oracle."
acknowledgement: "We are grateful to Devika Sharma and Luca Trevisan for their insight
  and advice and to an anonymous reviewer for helpful comments.\r\n\r\nThis work was
  supported by the European Research Council (ERC) under the European Union’s Horizon
  2020 research and innovation programme (Grant agreement No. 101019547). The first
  author was additionally supported by RGC GRF CUHK14209920 and the fourth author
  was additionally supported by ISF grant No. 1399/17, project PROMETHEUS (Grant 780701),
  and Cariplo CRYPTONOMEX grant."
alternative_title:
- LNCS
article_processing_charge: No
author:
- first_name: Andrej
  full_name: Bogdanov, Andrej
  last_name: Bogdanov
- first_name: Miguel
  full_name: Cueto Noval, Miguel
  id: ffc563a3-f6e0-11ea-865d-e3cce03d17cc
  last_name: Cueto Noval
- first_name: Charlotte
  full_name: Hoffmann, Charlotte
  id: 0f78d746-dc7d-11ea-9b2f-83f92091afe7
  last_name: Hoffmann
- first_name: Alon
  full_name: Rosen, Alon
  last_name: Rosen
citation:
  ama: 'Bogdanov A, Cueto Noval M, Hoffmann C, Rosen A. Public-Key Encryption from Homogeneous
    CLWE. In: <i>Theory of Cryptography</i>. Vol 13748. Springer Nature; 2022:565-592.
    doi:<a href="https://doi.org/10.1007/978-3-031-22365-5_20">10.1007/978-3-031-22365-5_20</a>'
  apa: 'Bogdanov, A., Cueto Noval, M., Hoffmann, C., &#38; Rosen, A. (2022). Public-Key
    Encryption from Homogeneous CLWE. In <i>Theory of Cryptography</i> (Vol. 13748,
    pp. 565–592). Chicago, IL, United States: Springer Nature. <a href="https://doi.org/10.1007/978-3-031-22365-5_20">https://doi.org/10.1007/978-3-031-22365-5_20</a>'
  chicago: Bogdanov, Andrej, Miguel Cueto Noval, Charlotte Hoffmann, and Alon Rosen.
    “Public-Key Encryption from Homogeneous CLWE.” In <i>Theory of Cryptography</i>,
    13748:565–92. Springer Nature, 2022. <a href="https://doi.org/10.1007/978-3-031-22365-5_20">https://doi.org/10.1007/978-3-031-22365-5_20</a>.
  ieee: A. Bogdanov, M. Cueto Noval, C. Hoffmann, and A. Rosen, “Public-Key Encryption
    from Homogeneous CLWE,” in <i>Theory of Cryptography</i>, Chicago, IL, United
    States, 2022, vol. 13748, pp. 565–592.
  ista: 'Bogdanov A, Cueto Noval M, Hoffmann C, Rosen A. 2022. Public-Key Encryption
    from Homogeneous CLWE. Theory of Cryptography. TCC: Theory of Cryptography, LNCS,
    vol. 13748, 565–592.'
  mla: Bogdanov, Andrej, et al. “Public-Key Encryption from Homogeneous CLWE.” <i>Theory
    of Cryptography</i>, vol. 13748, Springer Nature, 2022, pp. 565–92, doi:<a href="https://doi.org/10.1007/978-3-031-22365-5_20">10.1007/978-3-031-22365-5_20</a>.
  short: A. Bogdanov, M. Cueto Noval, C. Hoffmann, A. Rosen, in:, Theory of Cryptography,
    Springer Nature, 2022, pp. 565–592.
conference:
  end_date: 2022-11-10
  location: Chicago, IL, United States
  name: 'TCC: Theory of Cryptography'
  start_date: 2022-11-07
date_created: 2023-02-05T23:01:00Z
date_published: 2022-12-21T00:00:00Z
date_updated: 2023-08-04T10:39:30Z
day: '21'
department:
- _id: KrPi
doi: 10.1007/978-3-031-22365-5_20
external_id:
  isi:
  - '000921318200020'
intvolume: '     13748'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://eprint.iacr.org/2022/093
month: '12'
oa: 1
oa_version: Preprint
page: 565-592
publication: Theory of Cryptography
publication_identifier:
  eissn:
  - 1611-3349
  isbn:
  - '9783031223648'
  issn:
  - 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Public-Key Encryption from Homogeneous CLWE
type: conference
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 13748
year: '2022'
...
---
_id: '12522'
abstract:
- lang: eng
  text: This .zip File contains the transport data, the codes for the data analysis,
    the microscopy analysis and the codes for the theoretical simulations for "Majorana-like
    Coulomb spectroscopy in the absence of zero bias peaks" by M. Valentini, et. al.
    The transport data are saved with hdf5 file format. The files can be open with
    the log browser of Labber.
article_processing_charge: No
author:
- first_name: Marco
  full_name: Valentini, Marco
  id: C0BB2FAC-D767-11E9-B658-BC13E6697425
  last_name: Valentini
- first_name: Pablo
  full_name: San-Jose, Pablo
  last_name: San-Jose
- first_name: Jordi
  full_name: Arbiol, Jordi
  last_name: Arbiol
- first_name: Sara
  full_name: Marti-Sanchez, Sara
  last_name: Marti-Sanchez
- first_name: Marc
  full_name: Botifoll, Marc
  last_name: Botifoll
citation:
  ama: Valentini M, San-Jose P, Arbiol J, Marti-Sanchez S, Botifoll M. Data for “Majorana-like
    Coulomb spectroscopy in the absence of zero bias peaks.” 2022. doi:<a href="https://doi.org/10.15479/AT:ISTA:12102">10.15479/AT:ISTA:12102</a>
  apa: Valentini, M., San-Jose, P., Arbiol, J., Marti-Sanchez, S., &#38; Botifoll,
    M. (2022). Data for “Majorana-like Coulomb spectroscopy in the absence of zero
    bias peaks.” Institute of Science and Technology Austria. <a href="https://doi.org/10.15479/AT:ISTA:12102">https://doi.org/10.15479/AT:ISTA:12102</a>
  chicago: Valentini, Marco, Pablo San-Jose, Jordi Arbiol, Sara Marti-Sanchez, and
    Marc Botifoll. “Data for ‘Majorana-like Coulomb Spectroscopy in the Absence of
    Zero Bias Peaks.’” Institute of Science and Technology Austria, 2022. <a href="https://doi.org/10.15479/AT:ISTA:12102">https://doi.org/10.15479/AT:ISTA:12102</a>.
  ieee: M. Valentini, P. San-Jose, J. Arbiol, S. Marti-Sanchez, and M. Botifoll, “Data
    for ‘Majorana-like Coulomb spectroscopy in the absence of zero bias peaks.’” Institute
    of Science and Technology Austria, 2022.
  ista: Valentini M, San-Jose P, Arbiol J, Marti-Sanchez S, Botifoll M. 2022. Data
    for ‘Majorana-like Coulomb spectroscopy in the absence of zero bias peaks’, Institute
    of Science and Technology Austria, <a href="https://doi.org/10.15479/AT:ISTA:12102">10.15479/AT:ISTA:12102</a>.
  mla: Valentini, Marco, et al. <i>Data for “Majorana-like Coulomb Spectroscopy in
    the Absence of Zero Bias Peaks.”</i> Institute of Science and Technology Austria,
    2022, doi:<a href="https://doi.org/10.15479/AT:ISTA:12102">10.15479/AT:ISTA:12102</a>.
  short: M. Valentini, P. San-Jose, J. Arbiol, S. Marti-Sanchez, M. Botifoll, (2022).
contributor:
- contributor_type: contact_person
  first_name: Marco
  id: C0BB2FAC-D767-11E9-B658-BC13E6697425
  last_name: Valentini
date_created: 2023-02-07T08:13:39Z
date_published: 2022-09-25T00:00:00Z
date_updated: 2024-02-21T12:35:34Z
day: '25'
ddc:
- '530'
department:
- _id: GeKa
doi: 10.15479/AT:ISTA:12102
file:
- access_level: open_access
  checksum: 0dbd6327bf84c7e81b295c4bc9d12826
  content_type: application/x-zip-compressed
  creator: dernst
  date_created: 2023-02-07T08:18:24Z
  date_updated: 2023-02-07T08:18:24Z
  file_id: '12523'
  file_name: Majorana_like.zip
  file_size: 3609122411
  relation: main_file
  success: 1
file_date_updated: 2023-02-07T08:18:24Z
has_accepted_license: '1'
month: '09'
oa: 1
oa_version: Published Version
publisher: Institute of Science and Technology Austria
related_material:
  record:
  - id: '12118'
    relation: used_in_publication
    status: public
  - id: '13286'
    relation: used_in_publication
    status: public
status: public
title: Data for "Majorana-like Coulomb spectroscopy in the absence of zero bias peaks"
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
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2022'
...
---
_id: '12536'
abstract:
- lang: eng
  text: 'We consider the problem of estimating a rank-1 signal corrupted by structured
    rotationally invariant noise, and address the following question: how well do
    inference algorithms perform when the noise statistics is unknown and hence Gaussian
    noise is assumed? While the matched Bayes-optimal setting with unstructured noise
    is well understood, the analysis of this mismatched problem is only at its premises.
    In this paper, we make a step towards understanding the effect of the strong source
    of mismatch which is the noise statistics. Our main technical contribution is
    the rigorous analysis of a Bayes estimator and of an approximate message passing
    (AMP) algorithm, both of which incorrectly assume a Gaussian setup. The first
    result exploits the theory of spherical integrals and of low-rank matrix perturbations;
    the idea behind the second one is to design and analyze an artificial AMP which,
    by taking advantage of the flexibility in the denoisers, is able to "correct"
    the mismatch. Armed with these sharp asymptotic characterizations, we unveil a
    rich and often unexpected phenomenology. For example, despite AMP is in principle
    designed to efficiently compute the Bayes estimator, the former is outperformed
    by the latter in terms of mean-square error. We show that this performance gap
    is due to an incorrect estimation of the signal norm. In fact, when the SNR is
    large enough, the overlaps of the AMP and the Bayes estimator coincide, and they
    even match those of optimal estimators taking into account the structure of the
    noise.'
article_number: '2205.10009'
article_processing_charge: No
arxiv: 1
author:
- first_name: Jean
  full_name: Barbier, Jean
  last_name: Barbier
- first_name: TianQi
  full_name: Hou, TianQi
  last_name: Hou
- first_name: Marco
  full_name: Mondelli, Marco
  id: 27EB676C-8706-11E9-9510-7717E6697425
  last_name: Mondelli
  orcid: 0000-0002-3242-7020
- first_name: Manuel
  full_name: Saenz, Manuel
  last_name: Saenz
citation:
  ama: 'Barbier J, Hou T, Mondelli M, Saenz M. The price of ignorance: How much does
    it cost to forget noise structure in low-rank matrix estimation? <i>arXiv</i>.
    doi:<a href="https://doi.org/10.48550/arXiv.2205.10009">10.48550/arXiv.2205.10009</a>'
  apa: 'Barbier, J., Hou, T., Mondelli, M., &#38; Saenz, M. (n.d.). The price of ignorance:
    How much does it cost to forget noise structure in low-rank matrix estimation?
    <i>arXiv</i>. <a href="https://doi.org/10.48550/arXiv.2205.10009">https://doi.org/10.48550/arXiv.2205.10009</a>'
  chicago: 'Barbier, Jean, TianQi Hou, Marco Mondelli, and Manuel Saenz. “The Price
    of Ignorance: How Much Does It Cost to Forget Noise Structure in Low-Rank Matrix
    Estimation?” <i>ArXiv</i>, n.d. <a href="https://doi.org/10.48550/arXiv.2205.10009">https://doi.org/10.48550/arXiv.2205.10009</a>.'
  ieee: 'J. Barbier, T. Hou, M. Mondelli, and M. Saenz, “The price of ignorance: How
    much does it cost to forget noise structure in low-rank matrix estimation?,” <i>arXiv</i>.
    .'
  ista: 'Barbier J, Hou T, Mondelli M, Saenz M. The price of ignorance: How much does
    it cost to forget noise structure in low-rank matrix estimation? arXiv, 2205.10009.'
  mla: 'Barbier, Jean, et al. “The Price of Ignorance: How Much Does It Cost to Forget
    Noise Structure in Low-Rank Matrix Estimation?” <i>ArXiv</i>, 2205.10009, doi:<a
    href="https://doi.org/10.48550/arXiv.2205.10009">10.48550/arXiv.2205.10009</a>.'
  short: J. Barbier, T. Hou, M. Mondelli, M. Saenz, ArXiv (n.d.).
date_created: 2023-02-10T13:45:41Z
date_published: 2022-05-20T00:00:00Z
date_updated: 2023-02-16T09:41:25Z
day: '20'
department:
- _id: MaMo
doi: 10.48550/arXiv.2205.10009
external_id:
  arxiv:
  - '2205.10009'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://doi.org/10.48550/arXiv.2205.10009
month: '05'
oa: 1
oa_version: Preprint
publication: arXiv
publication_status: accepted
status: public
title: 'The price of ignorance: How much does it cost to forget noise structure in
  low-rank matrix estimation?'
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2022'
...
---
_id: '12537'
abstract:
- lang: eng
  text: 'The Neural Tangent Kernel (NTK) has emerged as a powerful tool to provide
    memorization, optimization and generalization guarantees in deep neural networks.
    A line of work has studied the NTK spectrum for two-layer and deep networks with
    at least a layer with Ω(N) neurons, N being the number of training samples. Furthermore,
    there is increasing evidence suggesting that deep networks with sub-linear layer
    widths are powerful memorizers and optimizers, as long as the number of parameters
    exceeds the number of samples. Thus, a natural open question is whether the NTK
    is well conditioned in such a challenging sub-linear setup. In this paper, we
    answer this question in the affirmative. Our key technical contribution is a lower
    bound on the smallest NTK eigenvalue for deep networks with the minimum possible
    over-parameterization: the number of parameters is roughly Ω(N) and, hence, the
    number of neurons is as little as Ω(N−−√). To showcase the applicability of our
    NTK bounds, we provide two results concerning memorization capacity and optimization
    guarantees for gradient descent training.'
acknowledgement: "The authors were partially supported by the 2019 Lopez-Loreta prize,
  and they would like to thank\r\nQuynh Nguyen, Mahdi Soltanolkotabi and Adel Javanmard
  for helpful discussions.\r\n"
article_processing_charge: No
arxiv: 1
author:
- first_name: Simone
  full_name: Bombari, Simone
  id: ca726dda-de17-11ea-bc14-f9da834f63aa
  last_name: Bombari
- first_name: Mohammad Hossein
  full_name: Amani, Mohammad Hossein
  last_name: Amani
- first_name: Marco
  full_name: Mondelli, Marco
  id: 27EB676C-8706-11E9-9510-7717E6697425
  last_name: Mondelli
  orcid: 0000-0002-3242-7020
citation:
  ama: 'Bombari S, Amani MH, Mondelli M. Memorization and optimization in deep neural
    networks with minimum over-parameterization. In: <i>36th Conference on Neural
    Information Processing Systems</i>. Vol 35. Curran Associates; 2022:7628-7640.'
  apa: Bombari, S., Amani, M. H., &#38; Mondelli, M. (2022). Memorization and optimization
    in deep neural networks with minimum over-parameterization. In <i>36th Conference
    on Neural Information Processing Systems</i> (Vol. 35, pp. 7628–7640). Curran
    Associates.
  chicago: Bombari, Simone, Mohammad Hossein Amani, and Marco Mondelli. “Memorization
    and Optimization in Deep Neural Networks with Minimum Over-Parameterization.”
    In <i>36th Conference on Neural Information Processing Systems</i>, 35:7628–40.
    Curran Associates, 2022.
  ieee: S. Bombari, M. H. Amani, and M. Mondelli, “Memorization and optimization in
    deep neural networks with minimum over-parameterization,” in <i>36th Conference
    on Neural Information Processing Systems</i>, 2022, vol. 35, pp. 7628–7640.
  ista: Bombari S, Amani MH, Mondelli M. 2022. Memorization and optimization in deep
    neural networks with minimum over-parameterization. 36th Conference on Neural
    Information Processing Systems. vol. 35, 7628–7640.
  mla: Bombari, Simone, et al. “Memorization and Optimization in Deep Neural Networks
    with Minimum Over-Parameterization.” <i>36th Conference on Neural Information
    Processing Systems</i>, vol. 35, Curran Associates, 2022, pp. 7628–40.
  short: S. Bombari, M.H. Amani, M. Mondelli, in:, 36th Conference on Neural Information
    Processing Systems, Curran Associates, 2022, pp. 7628–7640.
date_created: 2023-02-10T13:46:37Z
date_published: 2022-07-24T00:00:00Z
date_updated: 2024-09-10T13:03:19Z
day: '24'
department:
- _id: MaMo
external_id:
  arxiv:
  - '2205.10217'
intvolume: '        35'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: ' https://doi.org/10.48550/arXiv.2205.10217'
month: '07'
oa: 1
oa_version: Preprint
page: 7628-7640
project:
- _id: 059876FA-7A3F-11EA-A408-12923DDC885E
  name: Prix Lopez-Loretta 2019 - Marco Mondelli
publication: 36th Conference on Neural Information Processing Systems
publication_identifier:
  isbn:
  - '9781713871088'
publication_status: published
publisher: Curran Associates
quality_controlled: '1'
status: public
title: Memorization and optimization in deep neural networks with minimum over-parameterization
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 35
year: '2022'
...
---
_id: '12538'
abstract:
- lang: eng
  text: In this paper, we study the compression of a target two-layer neural network
    with N nodes into a compressed network with M<N nodes. More precisely, we consider
    the setting in which the weights of the target network are i.i.d. sub-Gaussian,
    and we minimize the population L_2 loss between the outputs of the target and
    of the compressed network, under the assumption of Gaussian inputs. By using tools
    from high-dimensional probability, we show that this non-convex problem can be
    simplified when the target network is sufficiently over-parameterized, and provide
    the error rate of this approximation as a function of the input dimension and
    N. In this mean-field limit, the simplified objective, as well as the optimal
    weights of the compressed network, does not depend on the realization of the target
    network, but only on expected scaling factors. Furthermore, for networks with
    ReLU activation, we conjecture that the optimum of the simplified optimization
    problem is achieved by taking weights on the Equiangular Tight Frame (ETF), while
    the scaling of the weights and the orientation of the ETF depend on the parameters
    of the target network. Numerical evidence is provided to support this conjecture.
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Mohammad Hossein
  full_name: Amani, Mohammad Hossein
  last_name: Amani
- first_name: Simone
  full_name: Bombari, Simone
  id: ca726dda-de17-11ea-bc14-f9da834f63aa
  last_name: Bombari
- first_name: Marco
  full_name: Mondelli, Marco
  id: 27EB676C-8706-11E9-9510-7717E6697425
  last_name: Mondelli
  orcid: 0000-0002-3242-7020
- first_name: Rattana
  full_name: Pukdee, Rattana
  last_name: Pukdee
- first_name: Stefano
  full_name: Rini, Stefano
  last_name: Rini
citation:
  ama: Amani MH, Bombari S, Mondelli M, Pukdee R, Rini S. Sharp asymptotics on the
    compression of two-layer neural networks. <i>IEEE Information Theory Workshop</i>.
    2022:588-593. doi:<a href="https://doi.org/10.1109/ITW54588.2022.9965870">10.1109/ITW54588.2022.9965870</a>
  apa: 'Amani, M. H., Bombari, S., Mondelli, M., Pukdee, R., &#38; Rini, S. (2022).
    Sharp asymptotics on the compression of two-layer neural networks. <i>IEEE Information
    Theory Workshop</i>. Mumbai, India: IEEE. <a href="https://doi.org/10.1109/ITW54588.2022.9965870">https://doi.org/10.1109/ITW54588.2022.9965870</a>'
  chicago: Amani, Mohammad Hossein, Simone Bombari, Marco Mondelli, Rattana Pukdee,
    and Stefano Rini. “Sharp Asymptotics on the Compression of Two-Layer Neural Networks.”
    <i>IEEE Information Theory Workshop</i>. IEEE, 2022. <a href="https://doi.org/10.1109/ITW54588.2022.9965870">https://doi.org/10.1109/ITW54588.2022.9965870</a>.
  ieee: M. H. Amani, S. Bombari, M. Mondelli, R. Pukdee, and S. Rini, “Sharp asymptotics
    on the compression of two-layer neural networks,” <i>IEEE Information Theory Workshop</i>.
    IEEE, pp. 588–593, 2022.
  ista: Amani MH, Bombari S, Mondelli M, Pukdee R, Rini S. 2022. Sharp asymptotics
    on the compression of two-layer neural networks. IEEE Information Theory Workshop.,
    588–593.
  mla: Amani, Mohammad Hossein, et al. “Sharp Asymptotics on the Compression of Two-Layer
    Neural Networks.” <i>IEEE Information Theory Workshop</i>, IEEE, 2022, pp. 588–93,
    doi:<a href="https://doi.org/10.1109/ITW54588.2022.9965870">10.1109/ITW54588.2022.9965870</a>.
  short: M.H. Amani, S. Bombari, M. Mondelli, R. Pukdee, S. Rini, IEEE Information
    Theory Workshop (2022) 588–593.
conference:
  end_date: 2022-11-09
  location: Mumbai, India
  name: 'ITW: Information Theory Workshop'
  start_date: 2022-11-01
date_created: 2023-02-10T13:47:56Z
date_published: 2022-11-16T00:00:00Z
date_updated: 2023-12-18T11:31:47Z
day: '16'
department:
- _id: MaMo
doi: 10.1109/ITW54588.2022.9965870
external_id:
  arxiv:
  - '2205.08199'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: ' https://doi.org/10.48550/arXiv.2205.08199'
month: '11'
oa: 1
oa_version: Preprint
page: 588-593
publication: IEEE Information Theory Workshop
publication_identifier:
  isbn:
  - '9781665483414'
publication_status: published
publisher: IEEE
quality_controlled: '1'
scopus_import: '1'
status: public
title: Sharp asymptotics on the compression of two-layer neural networks
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2022'
...
---
_id: '12540'
abstract:
- lang: eng
  text: We consider the problem of signal estimation in generalized linear models
    defined via rotationally invariant design matrices. Since these matrices can have
    an arbitrary spectral distribution, this model is well suited for capturing complex
    correlation structures which often arise in applications. We propose a novel family
    of approximate message passing (AMP) algorithms for signal estimation, and rigorously
    characterize their performance in the high-dimensional limit via a state evolution
    recursion. Our rotationally invariant AMP has complexity of the same order as
    the existing AMP derived under the restrictive assumption of a Gaussian design;
    our algorithm also recovers this existing AMP as a special case. Numerical results
    showcase a performance close to Vector AMP (which is conjectured to be Bayes-optimal
    in some settings), but obtained with a much lower complexity, as the proposed
    algorithm does not require a computationally expensive singular value decomposition.
acknowledgement: The authors would like to thank the anonymous reviewers for their
  helpful comments. KK and MM were partially supported by the 2019 Lopez-Loreta Prize.
article_number: '22'
article_processing_charge: No
author:
- first_name: Ramji
  full_name: Venkataramanan, Ramji
  last_name: Venkataramanan
- first_name: Kevin
  full_name: Kögler, Kevin
  id: 94ec913c-dc85-11ea-9058-e5051ab2428b
  last_name: Kögler
- first_name: Marco
  full_name: Mondelli, Marco
  id: 27EB676C-8706-11E9-9510-7717E6697425
  last_name: Mondelli
  orcid: 0000-0002-3242-7020
citation:
  ama: 'Venkataramanan R, Kögler K, Mondelli M. Estimation in rotationally invariant
    generalized linear models via approximate message passing. In: <i>Proceedings
    of the 39th International Conference on Machine Learning</i>. Vol 162. ML Research
    Press; 2022.'
  apa: 'Venkataramanan, R., Kögler, K., &#38; Mondelli, M. (2022). Estimation in rotationally
    invariant generalized linear models via approximate message passing. In <i>Proceedings
    of the 39th International Conference on Machine Learning</i> (Vol. 162). Baltimore,
    MD, United States: ML Research Press.'
  chicago: Venkataramanan, Ramji, Kevin Kögler, and Marco Mondelli. “Estimation in
    Rotationally Invariant Generalized Linear Models via Approximate Message Passing.”
    In <i>Proceedings of the 39th International Conference on Machine Learning</i>,
    Vol. 162. ML Research Press, 2022.
  ieee: R. Venkataramanan, K. Kögler, and M. Mondelli, “Estimation in rotationally
    invariant generalized linear models via approximate message passing,” in <i>Proceedings
    of the 39th International Conference on Machine Learning</i>, Baltimore, MD, United
    States, 2022, vol. 162.
  ista: 'Venkataramanan R, Kögler K, Mondelli M. 2022. Estimation in rotationally
    invariant generalized linear models via approximate message passing. Proceedings
    of the 39th International Conference on Machine Learning. ICML: International
    Conference on Machine Learning vol. 162, 22.'
  mla: Venkataramanan, Ramji, et al. “Estimation in Rotationally Invariant Generalized
    Linear Models via Approximate Message Passing.” <i>Proceedings of the 39th International
    Conference on Machine Learning</i>, vol. 162, 22, ML Research Press, 2022.
  short: R. Venkataramanan, K. Kögler, M. Mondelli, in:, Proceedings of the 39th International
    Conference on Machine Learning, ML Research Press, 2022.
conference:
  end_date: 2022-07-23
  location: Baltimore, MD, United States
  name: 'ICML: International Conference on Machine Learning'
  start_date: 2022-07-17
date_created: 2023-02-10T13:49:04Z
date_published: 2022-01-01T00:00:00Z
date_updated: 2024-09-10T13:03:17Z
ddc:
- '000'
department:
- _id: MaMo
file:
- access_level: open_access
  checksum: 67436eb0a660789514cdf9db79e84683
  content_type: application/pdf
  creator: dernst
  date_created: 2023-02-13T10:53:11Z
  date_updated: 2023-02-13T10:53:11Z
  file_id: '12547'
  file_name: 2022_PMLR_Venkataramanan.pdf
  file_size: 2341343
  relation: main_file
  success: 1
file_date_updated: 2023-02-13T10:53:11Z
has_accepted_license: '1'
intvolume: '       162'
language:
- iso: eng
oa: 1
oa_version: Published Version
project:
- _id: 059876FA-7A3F-11EA-A408-12923DDC885E
  name: Prix Lopez-Loretta 2019 - Marco Mondelli
publication: Proceedings of the 39th International Conference on Machine Learning
publication_status: published
publisher: ML Research Press
quality_controlled: '1'
status: public
title: Estimation in rotationally invariant generalized linear models via approximate
  message passing
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 162
year: '2022'
...
---
_id: '12568'
abstract:
- lang: eng
  text: We treat the problem of risk-aware control for stochastic shortest path (SSP)
    on Markov decision processes (MDP). Typically, expectation is considered for SSP,
    which however is oblivious to the incurred risk. We present an alternative view,
    instead optimizing conditional value-at-risk (CVaR), an established risk measure.
    We treat both Markov chains as well as MDP and introduce, through novel insights,
    two algorithms, based on linear programming and value iteration, respectively.
    Both algorithms offer precise and provably correct solutions. Evaluation of our
    prototype implementation shows that risk-aware control is feasible on several
    moderately sized models.
article_processing_charge: No
arxiv: 1
author:
- first_name: Tobias
  full_name: Meggendorfer, Tobias
  id: b21b0c15-30a2-11eb-80dc-f13ca25802e1
  last_name: Meggendorfer
  orcid: 0000-0002-1712-2165
citation:
  ama: 'Meggendorfer T. Risk-aware stochastic shortest path. In: <i>Proceedings of
    the 36th AAAI Conference on Artificial Intelligence, AAAI 2022</i>. Vol 36. Association
    for the Advancement of Artificial Intelligence; 2022:9858-9867. doi:<a href="https://doi.org/10.1609/aaai.v36i9.21222">10.1609/aaai.v36i9.21222</a>'
  apa: 'Meggendorfer, T. (2022). Risk-aware stochastic shortest path. In <i>Proceedings
    of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022</i> (Vol. 36,
    pp. 9858–9867). Virtual: Association for the Advancement of Artificial Intelligence.
    <a href="https://doi.org/10.1609/aaai.v36i9.21222">https://doi.org/10.1609/aaai.v36i9.21222</a>'
  chicago: Meggendorfer, Tobias. “Risk-Aware Stochastic Shortest Path.” In <i>Proceedings
    of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022</i>, 36:9858–67.
    Association for the Advancement of Artificial Intelligence, 2022. <a href="https://doi.org/10.1609/aaai.v36i9.21222">https://doi.org/10.1609/aaai.v36i9.21222</a>.
  ieee: T. Meggendorfer, “Risk-aware stochastic shortest path,” in <i>Proceedings
    of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022</i>, Virtual,
    2022, vol. 36, no. 9, pp. 9858–9867.
  ista: Meggendorfer T. 2022. Risk-aware stochastic shortest path. Proceedings of
    the 36th AAAI Conference on Artificial Intelligence, AAAI 2022. Conference on
    Artificial Intelligence vol. 36, 9858–9867.
  mla: Meggendorfer, Tobias. “Risk-Aware Stochastic Shortest Path.” <i>Proceedings
    of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022</i>, vol. 36,
    no. 9, Association for the Advancement of Artificial Intelligence, 2022, pp. 9858–67,
    doi:<a href="https://doi.org/10.1609/aaai.v36i9.21222">10.1609/aaai.v36i9.21222</a>.
  short: T. Meggendorfer, in:, Proceedings of the 36th AAAI Conference on Artificial
    Intelligence, AAAI 2022, Association for the Advancement of Artificial Intelligence,
    2022, pp. 9858–9867.
conference:
  end_date: 2022-03-01
  location: Virtual
  name: Conference on Artificial Intelligence
  start_date: 2022-02-22
date_created: 2023-02-19T23:00:56Z
date_published: 2022-06-28T00:00:00Z
date_updated: 2023-02-20T07:19:12Z
day: '28'
department:
- _id: KrCh
doi: 10.1609/aaai.v36i9.21222
external_id:
  arxiv:
  - '2203.01640'
intvolume: '        36'
issue: '9'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: ' https://doi.org/10.48550/arXiv.2203.01640'
month: '06'
oa: 1
oa_version: Preprint
page: 9858-9867
publication: Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI
  2022
publication_identifier:
  eissn:
  - 2374-3468
  isbn:
  - '1577358767'
publication_status: published
publisher: Association for the Advancement of Artificial Intelligence
quality_controlled: '1'
scopus_import: '1'
status: public
title: Risk-aware stochastic shortest path
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 36
year: '2022'
...
---
_id: '12660'
abstract:
- lang: eng
  text: 'We present Cross-Client Label Propagation(XCLP), a new method for transductive
    federated learning. XCLP estimates a data graph jointly from the data of multiple
    clients and computes labels for the unlabeled data by propagating label information
    across the graph. To avoid clients having to share their data with anyone, XCLP
    employs two cryptographically secure protocols: secure Hamming distance computation
    and secure summation. We demonstrate two distinct applications of XCLP within
    federated learning. In the first, we use it in a one-shot way to predict labels
    for unseen test points. In the second, we use it to repeatedly pseudo-label unlabeled
    training data in a federated semi-supervised setting. Experiments on both real
    federated and standard benchmark datasets show that in both applications XCLP
    achieves higher classification accuracy than alternative approaches.'
article_number: '2210.06434'
article_processing_charge: No
arxiv: 1
author:
- first_name: Jonathan A
  full_name: Scott, Jonathan A
  id: e499926b-f6e0-11ea-865d-9c63db0031e8
  last_name: Scott
- first_name: Michelle X
  full_name: Yeo, Michelle X
  id: 2D82B818-F248-11E8-B48F-1D18A9856A87
  last_name: Yeo
- first_name: Christoph
  full_name: Lampert, Christoph
  id: 40C20FD2-F248-11E8-B48F-1D18A9856A87
  last_name: Lampert
  orcid: 0000-0001-8622-7887
citation:
  ama: Scott JA, Yeo MX, Lampert C. Cross-client Label Propagation for transductive
    federated learning. <i>arXiv</i>. doi:<a href="https://doi.org/10.48550/arXiv.2210.06434">10.48550/arXiv.2210.06434</a>
  apa: Scott, J. A., Yeo, M. X., &#38; Lampert, C. (n.d.). Cross-client Label Propagation
    for transductive federated learning. <i>arXiv</i>. <a href="https://doi.org/10.48550/arXiv.2210.06434">https://doi.org/10.48550/arXiv.2210.06434</a>
  chicago: Scott, Jonathan A, Michelle X Yeo, and Christoph Lampert. “Cross-Client
    Label Propagation for Transductive Federated Learning.” <i>ArXiv</i>, n.d. <a
    href="https://doi.org/10.48550/arXiv.2210.06434">https://doi.org/10.48550/arXiv.2210.06434</a>.
  ieee: J. A. Scott, M. X. Yeo, and C. Lampert, “Cross-client Label Propagation for
    transductive federated learning,” <i>arXiv</i>. .
  ista: Scott JA, Yeo MX, Lampert C. Cross-client Label Propagation for transductive
    federated learning. arXiv, 2210.06434.
  mla: Scott, Jonathan A., et al. “Cross-Client Label Propagation for Transductive
    Federated Learning.” <i>ArXiv</i>, 2210.06434, doi:<a href="https://doi.org/10.48550/arXiv.2210.06434">10.48550/arXiv.2210.06434</a>.
  short: J.A. Scott, M.X. Yeo, C. Lampert, ArXiv (n.d.).
date_created: 2023-02-20T08:21:50Z
date_published: 2022-10-12T00:00:00Z
date_updated: 2023-02-21T08:20:18Z
day: '12'
ddc:
- '004'
department:
- _id: ChLa
doi: 10.48550/arXiv.2210.06434
external_id:
  arxiv:
  - '2210.06434'
file:
- access_level: open_access
  checksum: 7ab20543fd4393f14fb857ce2e4f03c6
  content_type: application/pdf
  creator: chl
  date_created: 2023-02-20T08:21:35Z
  date_updated: 2023-02-20T08:21:35Z
  file_id: '12661'
  file_name: 2210.06434.pdf
  file_size: 291893
  relation: main_file
  success: 1
file_date_updated: 2023-02-20T08:21:35Z
has_accepted_license: '1'
language:
- iso: eng
month: '10'
oa: 1
oa_version: Preprint
publication: arXiv
publication_status: submitted
status: public
title: Cross-client Label Propagation for transductive federated learning
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: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2022'
...
---
_id: '12662'
abstract:
- lang: eng
  text: 'Modern machine learning tasks often require considering not just one but
    multiple objectives. For example, besides the prediction quality, this could be
    the efficiency, robustness or fairness of the learned models, or any of their
    combinations. Multi-objective learning offers a natural framework for handling
    such problems without having to commit to early trade-offs. Surprisingly, statistical
    learning theory so far offers almost no insight into the generalization properties
    of multi-objective learning. In this work, we make first steps to fill this gap:
    we establish foundational generalization bounds for the multi-objective setting
    as well as generalization and excess bounds for learning with scalarizations.
    We also provide the first theoretical analysis of the relation between the Pareto-optimal
    sets of the true objectives and the Pareto-optimal sets of their empirical approximations
    from training data. In particular, we show a surprising asymmetry: all Pareto-optimal
    solutions can be approximated by empirically Pareto-optimal ones, but not vice
    versa.'
article_number: '2208.13499'
article_processing_charge: No
arxiv: 1
author:
- first_name: Peter
  full_name: Súkeník, Peter
  id: d64d6a8d-eb8e-11eb-b029-96fd216dec3c
  last_name: Súkeník
- first_name: Christoph
  full_name: Lampert, Christoph
  id: 40C20FD2-F248-11E8-B48F-1D18A9856A87
  last_name: Lampert
  orcid: 0000-0001-8622-7887
citation:
  ama: Súkeník P, Lampert C. Generalization in Multi-objective machine learning. <i>arXiv</i>.
    doi:<a href="https://doi.org/10.48550/arXiv.2208.13499">10.48550/arXiv.2208.13499</a>
  apa: Súkeník, P., &#38; Lampert, C. (n.d.). Generalization in Multi-objective machine
    learning. <i>arXiv</i>. <a href="https://doi.org/10.48550/arXiv.2208.13499">https://doi.org/10.48550/arXiv.2208.13499</a>
  chicago: Súkeník, Peter, and Christoph Lampert. “Generalization in Multi-Objective
    Machine Learning.” <i>ArXiv</i>, n.d. <a href="https://doi.org/10.48550/arXiv.2208.13499">https://doi.org/10.48550/arXiv.2208.13499</a>.
  ieee: P. Súkeník and C. Lampert, “Generalization in Multi-objective machine learning,”
    <i>arXiv</i>. .
  ista: Súkeník P, Lampert C. Generalization in Multi-objective machine learning.
    arXiv, 2208.13499.
  mla: Súkeník, Peter, and Christoph Lampert. “Generalization in Multi-Objective Machine
    Learning.” <i>ArXiv</i>, 2208.13499, doi:<a href="https://doi.org/10.48550/arXiv.2208.13499">10.48550/arXiv.2208.13499</a>.
  short: P. Súkeník, C. Lampert, ArXiv (n.d.).
date_created: 2023-02-20T08:23:06Z
date_published: 2022-08-29T00:00:00Z
date_updated: 2023-02-21T08:24:55Z
day: '29'
ddc:
- '004'
department:
- _id: ChLa
doi: 10.48550/arXiv.2208.13499
external_id:
  arxiv:
  - '2208.13499'
has_accepted_license: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: ' https://doi.org/10.48550/arXiv.2208.13499'
month: '08'
oa: 1
oa_version: Preprint
publication: arXiv
publication_status: submitted
status: public
title: Generalization in Multi-objective machine learning
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2022'
...
---
_id: '12670'
abstract:
- lang: eng
  text: DNA methylation plays essential homeostatic functions in eukaryotic genomes.
    In animals, DNA methylation is also developmentally regulated and, in turn, regulates
    development. In the past two decades, huge research effort has endorsed the understanding
    that DNA methylation plays a similar role in plant development, especially during
    sexual reproduction. The power of whole-genome sequencing and cell isolation techniques,
    as well as bioinformatics tools, have enabled recent studies to reveal dynamic
    changes in DNA methylation during germline development. Furthermore, the combination
    of these technological advances with genetics, developmental biology and cell
    biology tools has revealed functional methylation reprogramming events that control
    gene and transposon activities in flowering plant germlines. In this review, we
    discuss the major advances in our knowledge of DNA methylation dynamics during
    male and female germline development in flowering plants.
article_processing_charge: No
article_type: review
author:
- first_name: Shengbo
  full_name: He, Shengbo
  last_name: He
- first_name: Xiaoqi
  full_name: Feng, Xiaoqi
  id: e0164712-22ee-11ed-b12a-d80fcdf35958
  last_name: Feng
  orcid: 0000-0002-4008-1234
citation:
  ama: He S, Feng X. DNA methylation dynamics during germline development. <i>Journal
    of Integrative Plant Biology</i>. 2022;64(12):2240-2251. doi:<a href="https://doi.org/10.1111/jipb.13422">10.1111/jipb.13422</a>
  apa: He, S., &#38; Feng, X. (2022). DNA methylation dynamics during germline development.
    <i>Journal of Integrative Plant Biology</i>. Wiley. <a href="https://doi.org/10.1111/jipb.13422">https://doi.org/10.1111/jipb.13422</a>
  chicago: He, Shengbo, and Xiaoqi Feng. “DNA Methylation Dynamics during Germline
    Development.” <i>Journal of Integrative Plant Biology</i>. Wiley, 2022. <a href="https://doi.org/10.1111/jipb.13422">https://doi.org/10.1111/jipb.13422</a>.
  ieee: S. He and X. Feng, “DNA methylation dynamics during germline development,”
    <i>Journal of Integrative Plant Biology</i>, vol. 64, no. 12. Wiley, pp. 2240–2251,
    2022.
  ista: He S, Feng X. 2022. DNA methylation dynamics during germline development.
    Journal of Integrative Plant Biology. 64(12), 2240–2251.
  mla: He, Shengbo, and Xiaoqi Feng. “DNA Methylation Dynamics during Germline Development.”
    <i>Journal of Integrative Plant Biology</i>, vol. 64, no. 12, Wiley, 2022, pp.
    2240–51, doi:<a href="https://doi.org/10.1111/jipb.13422">10.1111/jipb.13422</a>.
  short: S. He, X. Feng, Journal of Integrative Plant Biology 64 (2022) 2240–2251.
date_created: 2023-02-23T09:15:57Z
date_published: 2022-12-07T00:00:00Z
date_updated: 2023-05-08T10:59:00Z
day: '07'
department:
- _id: XiFe
doi: 10.1111/jipb.13422
extern: '1'
external_id:
  pmid:
  - '36478632'
intvolume: '        64'
issue: '12'
keyword:
- Plant Science
- General Biochemistry
- Genetics and Molecular Biology
- Biochemistry
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://doi.org/10.1111/jipb.13422
month: '12'
oa: 1
oa_version: Published Version
page: 2240-2251
pmid: 1
publication: Journal of Integrative Plant Biology
publication_identifier:
  eissn:
  - 1744-7909
  issn:
  - 1672-9072
publication_status: published
publisher: Wiley
quality_controlled: '1'
scopus_import: '1'
status: public
title: DNA methylation dynamics during germline development
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 64
year: '2022'
...
---
_id: '12671'
abstract:
- lang: eng
  text: Sperm chromatin is typically transformed by protamines into a compact and
    transcriptionally inactive state1,2. Sperm cells of flowering plants lack protamines,
    yet they have small, transcriptionally active nuclei with chromatin condensed
    through an unknown mechanism3,4. Here we show that a histone variant, H2B.8, mediates
    sperm chromatin and nuclear condensation in Arabidopsis thaliana. Loss of H2B.8
    causes enlarged sperm nuclei with dispersed chromatin, whereas ectopic expression
    in somatic cells produces smaller nuclei with aggregated chromatin. This result
    demonstrates that H2B.8 is sufficient for chromatin condensation. H2B.8 aggregates
    transcriptionally inactive AT-rich chromatin into phase-separated condensates,
    which facilitates nuclear compaction without reducing transcription. Reciprocal
    crosses show that mutation of h2b.8 reduces male transmission, which suggests
    that H2B.8-mediated sperm compaction is important for fertility. Altogether, our
    results reveal a new mechanism of nuclear compaction through global aggregation
    of unexpressed chromatin. We propose that H2B.8 is an evolutionary innovation
    of flowering plants that achieves nuclear condensation compatible with active
    transcription.
article_processing_charge: No
article_type: original
author:
- first_name: Toby
  full_name: Buttress, Toby
  last_name: Buttress
- first_name: Shengbo
  full_name: He, Shengbo
  last_name: He
- first_name: Liang
  full_name: Wang, Liang
  last_name: Wang
- first_name: Shaoli
  full_name: Zhou, Shaoli
  last_name: Zhou
- first_name: Gerhard
  full_name: Saalbach, Gerhard
  last_name: Saalbach
- first_name: Martin
  full_name: Vickers, Martin
  last_name: Vickers
- first_name: Guohong
  full_name: Li, Guohong
  last_name: Li
- first_name: Pilong
  full_name: Li, Pilong
  last_name: Li
- first_name: Xiaoqi
  full_name: Feng, Xiaoqi
  id: e0164712-22ee-11ed-b12a-d80fcdf35958
  last_name: Feng
  orcid: 0000-0002-4008-1234
citation:
  ama: Buttress T, He S, Wang L, et al. Histone H2B.8 compacts flowering plant sperm
    through chromatin phase separation. <i>Nature</i>. 2022;611(7936):614-622. doi:<a
    href="https://doi.org/10.1038/s41586-022-05386-6">10.1038/s41586-022-05386-6</a>
  apa: Buttress, T., He, S., Wang, L., Zhou, S., Saalbach, G., Vickers, M., … Feng,
    X. (2022). Histone H2B.8 compacts flowering plant sperm through chromatin phase
    separation. <i>Nature</i>. Springer Nature. <a href="https://doi.org/10.1038/s41586-022-05386-6">https://doi.org/10.1038/s41586-022-05386-6</a>
  chicago: Buttress, Toby, Shengbo He, Liang Wang, Shaoli Zhou, Gerhard Saalbach,
    Martin Vickers, Guohong Li, Pilong Li, and Xiaoqi Feng. “Histone H2B.8 Compacts
    Flowering Plant Sperm through Chromatin Phase Separation.” <i>Nature</i>. Springer
    Nature, 2022. <a href="https://doi.org/10.1038/s41586-022-05386-6">https://doi.org/10.1038/s41586-022-05386-6</a>.
  ieee: T. Buttress <i>et al.</i>, “Histone H2B.8 compacts flowering plant sperm through
    chromatin phase separation,” <i>Nature</i>, vol. 611, no. 7936. Springer Nature,
    pp. 614–622, 2022.
  ista: Buttress T, He S, Wang L, Zhou S, Saalbach G, Vickers M, Li G, Li P, Feng
    X. 2022. Histone H2B.8 compacts flowering plant sperm through chromatin phase
    separation. Nature. 611(7936), 614–622.
  mla: Buttress, Toby, et al. “Histone H2B.8 Compacts Flowering Plant Sperm through
    Chromatin Phase Separation.” <i>Nature</i>, vol. 611, no. 7936, Springer Nature,
    2022, pp. 614–22, doi:<a href="https://doi.org/10.1038/s41586-022-05386-6">10.1038/s41586-022-05386-6</a>.
  short: T. Buttress, S. He, L. Wang, S. Zhou, G. Saalbach, M. Vickers, G. Li, P.
    Li, X. Feng, Nature 611 (2022) 614–622.
date_created: 2023-02-23T09:17:05Z
date_published: 2022-11-17T00:00:00Z
date_updated: 2023-05-08T10:59:22Z
day: '17'
department:
- _id: XiFe
doi: 10.1038/s41586-022-05386-6
extern: '1'
external_id:
  pmid:
  - '36323776'
intvolume: '       611'
issue: '7936'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://doi.org/10.1038/s41586-022-05386-6
month: '11'
oa: 1
oa_version: Published Version
page: 614-622
pmid: 1
publication: Nature
publication_identifier:
  eissn:
  - 1476-4687
  issn:
  - 0028-0836
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Histone H2B.8 compacts flowering plant sperm through chromatin phase separation
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 611
year: '2022'
...
---
_id: '12677'
abstract:
- lang: eng
  text: "In modern sample-driven Prophet Inequality, an adversary chooses a sequence
    of n items with values v1,v2,…,vn to be presented to a decision maker (DM). The
    process follows in two phases. In the first phase (sampling phase), some items,
    possibly selected at random, are revealed to the DM, but she can never accept
    them. In the second phase, the DM is presented with the other items in a random
    order and online fashion. For each item, she must make an irrevocable decision
    to either accept the item and stop the process or reject the item forever and
    proceed to the next item. The goal of the DM is to maximize the expected value
    as compared to a Prophet (or offline algorithm) that has access to all information.
    In this setting, the sampling phase has no cost and is not part of the optimization
    process. However, in many scenarios, the samples are obtained as part of the decision-making
    process.\r\nWe model this aspect as a two-phase Prophet Inequality where an adversary
    chooses a sequence of 2n items with values v1,v2,…,v2n and the items are randomly
    ordered. Finally, there are two phases of the Prophet Inequality problem with
    the first n-items and the rest of the items, respectively. We show that some basic
    algorithms achieve a ratio of at most 0.450. We present an algorithm that achieves
    a ratio of at least 0.495. Finally, we show that for every algorithm the ratio
    it can achieve is at most 0.502. Hence our algorithm is near-optimal."
acknowledgement: This research was partially supported by the ERC CoG 863818 (ForM-SMArt)
  grant.
article_number: '2209.14368'
article_processing_charge: No
arxiv: 1
author:
- first_name: Krishnendu
  full_name: Chatterjee, Krishnendu
  id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
  last_name: Chatterjee
  orcid: 0000-0002-4561-241X
- first_name: Mona
  full_name: Mohammadi, Mona
  id: 4363614d-b686-11ed-a7d5-ac9e4a24bc2e
  last_name: Mohammadi
- first_name: Raimundo J
  full_name: Saona Urmeneta, Raimundo J
  id: BD1DF4C4-D767-11E9-B658-BC13E6697425
  last_name: Saona Urmeneta
  orcid: 0000-0001-5103-038X
citation:
  ama: Chatterjee K, Mohammadi M, Saona Urmeneta RJ. Repeated prophet inequality with
    near-optimal bounds. <i>arXiv</i>. doi:<a href="https://doi.org/10.48550/ARXIV.2209.14368">10.48550/ARXIV.2209.14368</a>
  apa: Chatterjee, K., Mohammadi, M., &#38; Saona Urmeneta, R. J. (n.d.). Repeated
    prophet inequality with near-optimal bounds. <i>arXiv</i>. <a href="https://doi.org/10.48550/ARXIV.2209.14368">https://doi.org/10.48550/ARXIV.2209.14368</a>
  chicago: Chatterjee, Krishnendu, Mona Mohammadi, and Raimundo J Saona Urmeneta.
    “Repeated Prophet Inequality with Near-Optimal Bounds.” <i>ArXiv</i>, n.d. <a
    href="https://doi.org/10.48550/ARXIV.2209.14368">https://doi.org/10.48550/ARXIV.2209.14368</a>.
  ieee: K. Chatterjee, M. Mohammadi, and R. J. Saona Urmeneta, “Repeated prophet inequality
    with near-optimal bounds,” <i>arXiv</i>. .
  ista: Chatterjee K, Mohammadi M, Saona Urmeneta RJ. Repeated prophet inequality
    with near-optimal bounds. arXiv, 2209.14368.
  mla: Chatterjee, Krishnendu, et al. “Repeated Prophet Inequality with Near-Optimal
    Bounds.” <i>ArXiv</i>, 2209.14368, doi:<a href="https://doi.org/10.48550/ARXIV.2209.14368">10.48550/ARXIV.2209.14368</a>.
  short: K. Chatterjee, M. Mohammadi, R.J. Saona Urmeneta, ArXiv (n.d.).
date_created: 2023-02-24T12:21:40Z
date_published: 2022-09-28T00:00:00Z
date_updated: 2025-07-14T09:09:51Z
day: '28'
department:
- _id: GradSch
- _id: KrCh
doi: 10.48550/ARXIV.2209.14368
ec_funded: 1
external_id:
  arxiv:
  - '2209.14368'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: ' https://doi.org/10.48550/arXiv.2209.14368'
month: '09'
oa: 1
oa_version: Preprint
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
  call_identifier: H2020
  grant_number: '863818'
  name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
publication: arXiv
publication_status: submitted
status: public
title: Repeated prophet inequality with near-optimal bounds
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2022'
...
---
_id: '12684'
abstract:
- lang: eng
  text: Given a place  ω  of a global function field  K  over a finite field, with
    associated affine function ring  Rω  and completion  Kω , the aim of this paper
    is to give an effective joint equidistribution result for renormalized primitive
    lattice points  (a,b)∈Rω2  in the plane  Kω2 , and for renormalized solutions
    to the gcd equation  ax+by=1 . The main tools are techniques of Goronik and Nevo
    for counting lattice points in well-rounded families of subsets. This gives a
    sharper analog in positive characteristic of a result of Nevo and the first author
    for the equidistribution of the primitive lattice points in  \ZZ2 .
acknowledgement: "The authors warmly thank Amos Nevo for having presented the authors
  to each other during\r\na beautiful conference in Goa in February 2016, where the
  idea of this paper was born. The\r\nfirst author thanks the IHES for two post-doctoral
  years when most of this paper was discussed,\r\nand the Topology team in Orsay for
  financial support at the final stage. The first author was\r\nsupported by the EPRSC
  EP/P026710/1 grant. Finally, we warmly thank the referee for many\r\nvery helpful
  comments that have improved the readability of this paper."
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Tal
  full_name: Horesh, Tal
  id: C8B7BF48-8D81-11E9-BCA9-F536E6697425
  last_name: Horesh
- first_name: Frédéric
  full_name: Paulin, Frédéric
  last_name: Paulin
citation:
  ama: Horesh T, Paulin F. Effective equidistribution of lattice points in positive
    characteristic. <i>Journal de Theorie des Nombres de Bordeaux</i>. 2022;34(3):679-703.
    doi:<a href="https://doi.org/10.5802/JTNB.1222">10.5802/JTNB.1222</a>
  apa: Horesh, T., &#38; Paulin, F. (2022). Effective equidistribution of lattice
    points in positive characteristic. <i>Journal de Theorie Des Nombres de Bordeaux</i>.
    Centre Mersenne. <a href="https://doi.org/10.5802/JTNB.1222">https://doi.org/10.5802/JTNB.1222</a>
  chicago: Horesh, Tal, and Frédéric Paulin. “Effective Equidistribution of Lattice
    Points in Positive Characteristic.” <i>Journal de Theorie Des Nombres de Bordeaux</i>.
    Centre Mersenne, 2022. <a href="https://doi.org/10.5802/JTNB.1222">https://doi.org/10.5802/JTNB.1222</a>.
  ieee: T. Horesh and F. Paulin, “Effective equidistribution of lattice points in
    positive characteristic,” <i>Journal de Theorie des Nombres de Bordeaux</i>, vol.
    34, no. 3. Centre Mersenne, pp. 679–703, 2022.
  ista: Horesh T, Paulin F. 2022. Effective equidistribution of lattice points in
    positive characteristic. Journal de Theorie des Nombres de Bordeaux. 34(3), 679–703.
  mla: Horesh, Tal, and Frédéric Paulin. “Effective Equidistribution of Lattice Points
    in Positive Characteristic.” <i>Journal de Theorie Des Nombres de Bordeaux</i>,
    vol. 34, no. 3, Centre Mersenne, 2022, pp. 679–703, doi:<a href="https://doi.org/10.5802/JTNB.1222">10.5802/JTNB.1222</a>.
  short: T. Horesh, F. Paulin, Journal de Theorie Des Nombres de Bordeaux 34 (2022)
    679–703.
date_created: 2023-02-26T23:01:02Z
date_published: 2022-01-27T00:00:00Z
date_updated: 2023-08-04T10:41:40Z
day: '27'
ddc:
- '510'
department:
- _id: TiBr
doi: 10.5802/JTNB.1222
external_id:
  arxiv:
  - '2001.01534'
  isi:
  - '000926504300003'
file:
- access_level: open_access
  checksum: 08f28fded270251f568f610cf5166d69
  content_type: application/pdf
  creator: dernst
  date_created: 2023-02-27T09:10:13Z
  date_updated: 2023-02-27T09:10:13Z
  file_id: '12689'
  file_name: 2023_JourTheorieNombreBordeaux_Horesh.pdf
  file_size: 870468
  relation: main_file
  success: 1
file_date_updated: 2023-02-27T09:10:13Z
has_accepted_license: '1'
intvolume: '        34'
isi: 1
issue: '3'
language:
- iso: eng
license: https://creativecommons.org/licenses/by-nd/4.0/
month: '01'
oa: 1
oa_version: Published Version
page: 679-703
publication: Journal de Theorie des Nombres de Bordeaux
publication_identifier:
  eissn:
  - 2118-8572
  issn:
  - 1246-7405
publication_status: published
publisher: Centre Mersenne
quality_controlled: '1'
scopus_import: '1'
status: public
title: Effective equidistribution of lattice points in positive characteristic
tmp:
  image: /image/cc_by_nd.png
  legal_code_url: https://creativecommons.org/licenses/by-nd/4.0/legalcode
  name: Creative Commons Attribution-NoDerivatives 4.0 International (CC BY-ND 4.0)
  short: CC BY-ND (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 34
year: '2022'
...
---
_id: '12750'
abstract:
- lang: eng
  text: Quantum kinetically constrained models have recently attracted significant
    attention due to their anomalous dynamics and thermalization. In this work, we
    introduce a hitherto unexplored family of kinetically constrained models featuring
    a conserved particle number and strong inversion-symmetry breaking due to facilitated
    hopping. We demonstrate that these models provide a generic example of so-called
    quantum Hilbert space fragmentation, that is manifested in disconnected sectors
    in the Hilbert space that are not apparent in the computational basis. Quantum
    Hilbert space fragmentation leads to an exponential in system size number of eigenstates
    with exactly zero entanglement entropy across several bipartite cuts. These eigenstates
    can be probed dynamically using quenches from simple initial product states. In
    addition, we study the particle spreading under unitary dynamics launched from
    the domain wall state, and find faster than diffusive dynamics at high particle
    densities, that crosses over into logarithmically slow relaxation at smaller densities.
    Using a classically simulable cellular automaton, we reproduce the logarithmic
    dynamics observed in the quantum case. Our work suggests that particle conserving
    constrained models with inversion symmetry breaking realize so far unexplored
    universality classes of dynamics and invite their further theoretical and experimental
    studies.
article_number: '2210.15607'
article_processing_charge: No
arxiv: 1
author:
- first_name: Pietro
  full_name: Brighi, Pietro
  id: 4115AF5C-F248-11E8-B48F-1D18A9856A87
  last_name: Brighi
  orcid: 0000-0002-7969-2729
- first_name: Marko
  full_name: Ljubotina, Marko
  id: F75EE9BE-5C90-11EA-905D-16643DDC885E
  last_name: Ljubotina
  orcid: 0000-0003-0038-7068
- first_name: Maksym
  full_name: Serbyn, Maksym
  id: 47809E7E-F248-11E8-B48F-1D18A9856A87
  last_name: Serbyn
  orcid: 0000-0002-2399-5827
citation:
  ama: Brighi P, Ljubotina M, Serbyn M. Hilbert space fragmentation and slow dynamics
    in particle-conserving quantum East models. <i>arXiv</i>. doi:<a href="https://doi.org/10.48550/arXiv.2210.15607">10.48550/arXiv.2210.15607</a>
  apa: Brighi, P., Ljubotina, M., &#38; Serbyn, M. (n.d.). Hilbert space fragmentation
    and slow dynamics in particle-conserving quantum East models. <i>arXiv</i>. <a
    href="https://doi.org/10.48550/arXiv.2210.15607">https://doi.org/10.48550/arXiv.2210.15607</a>
  chicago: Brighi, Pietro, Marko Ljubotina, and Maksym Serbyn. “Hilbert Space Fragmentation
    and Slow Dynamics in Particle-Conserving Quantum East Models.” <i>ArXiv</i>, n.d.
    <a href="https://doi.org/10.48550/arXiv.2210.15607">https://doi.org/10.48550/arXiv.2210.15607</a>.
  ieee: P. Brighi, M. Ljubotina, and M. Serbyn, “Hilbert space fragmentation and slow
    dynamics in particle-conserving quantum East models,” <i>arXiv</i>. .
  ista: Brighi P, Ljubotina M, Serbyn M. Hilbert space fragmentation and slow dynamics
    in particle-conserving quantum East models. arXiv, 2210.15607.
  mla: Brighi, Pietro, et al. “Hilbert Space Fragmentation and Slow Dynamics in Particle-Conserving
    Quantum East Models.” <i>ArXiv</i>, 2210.15607, doi:<a href="https://doi.org/10.48550/arXiv.2210.15607">10.48550/arXiv.2210.15607</a>.
  short: P. Brighi, M. Ljubotina, M. Serbyn, ArXiv (n.d.).
date_created: 2023-03-23T14:33:13Z
date_published: 2022-11-07T00:00:00Z
date_updated: 2023-09-20T10:46:29Z
day: '07'
department:
- _id: GradSch
- _id: MaSe
doi: 10.48550/arXiv.2210.15607
external_id:
  arxiv:
  - '2210.15607'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://doi.org/10.48550/arXiv.2210.15607
month: '11'
oa: 1
oa_version: Preprint
publication: arXiv
publication_status: submitted
related_material:
  record:
  - id: '12732'
    relation: dissertation_contains
    status: public
  - id: '14334'
    relation: later_version
    status: public
status: public
title: Hilbert space fragmentation and slow dynamics in particle-conserving quantum
  East models
tmp:
  image: /images/cc_by_nc_sa.png
  legal_code_url: https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode
  name: Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC
    BY-NC-SA 4.0)
  short: CC BY-NC-SA (4.0)
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2022'
...
---
_id: '12775'
abstract:
- lang: eng
  text: "We consider the problem of approximating the reachability probabilities in
    Markov decision processes (MDP) with uncountable (continuous) state and action
    spaces. While there are algorithms that, for special classes of such MDP, provide
    a sequence of approximations converging to the true value in the limit, our aim
    is to obtain an algorithm with guarantees on the precision of the approximation.\r\nAs
    this problem is undecidable in general, assumptions on the MDP are necessary.
    Our main contribution is to identify sufficient assumptions that are as weak as
    possible, thus approaching the \"boundary\" of which systems can be correctly
    and reliably analyzed. To this end, we also argue why each of our assumptions
    is necessary for algorithms based on processing finitely many observations.\r\nWe
    present two solution variants. The first one provides converging lower bounds
    under weaker assumptions than typical ones from previous works concerned with
    guarantees. The second one then utilizes stronger assumptions to additionally
    provide converging upper bounds. Altogether, we obtain an anytime algorithm, i.e.
    yielding a sequence of approximants with known and iteratively improving precision,
    converging to the true value in the limit. Besides, due to the generality of our
    assumptions, our algorithms are very general templates, readily allowing for various
    heuristics from literature in contrast to, e.g., a specific discretization algorithm.
    Our theoretical contribution thus paves the way for future practical improvements
    without sacrificing correctness guarantees."
acknowledgement: "Kush Grover: The author has been supported by the DFG research training
  group GRK\r\n2428 ConVeY.\r\nMaximilian Weininger: The author has been partially
  supported by DFG projects 383882557\r\nStatistical Unbounded Verification (SUV)
  and 427755713 Group-By Objectives in Probabilistic\r\nVerification (GOPro)"
alternative_title:
- LIPIcs
article_number: '11'
article_processing_charge: No
arxiv: 1
author:
- first_name: Kush
  full_name: Grover, Kush
  last_name: Grover
- first_name: Jan
  full_name: Kretinsky, Jan
  id: 44CEF464-F248-11E8-B48F-1D18A9856A87
  last_name: Kretinsky
  orcid: 0000-0002-8122-2881
- first_name: Tobias
  full_name: Meggendorfer, Tobias
  id: b21b0c15-30a2-11eb-80dc-f13ca25802e1
  last_name: Meggendorfer
  orcid: 0000-0002-1712-2165
- first_name: Maimilian
  full_name: Weininger, Maimilian
  last_name: Weininger
citation:
  ama: 'Grover K, Kretinsky J, Meggendorfer T, Weininger M. Anytime guarantees for
    reachability in uncountable Markov decision processes. In: <i>33rd International
    Conference on Concurrency Theory </i>. Vol 243. Schloss Dagstuhl - Leibniz-Zentrum
    für Informatik; 2022. doi:<a href="https://doi.org/10.4230/LIPIcs.CONCUR.2022.11">10.4230/LIPIcs.CONCUR.2022.11</a>'
  apa: 'Grover, K., Kretinsky, J., Meggendorfer, T., &#38; Weininger, M. (2022). Anytime
    guarantees for reachability in uncountable Markov decision processes. In <i>33rd
    International Conference on Concurrency Theory </i> (Vol. 243). Warsaw, Poland:
    Schloss Dagstuhl - Leibniz-Zentrum für Informatik. <a href="https://doi.org/10.4230/LIPIcs.CONCUR.2022.11">https://doi.org/10.4230/LIPIcs.CONCUR.2022.11</a>'
  chicago: Grover, Kush, Jan Kretinsky, Tobias Meggendorfer, and Maimilian Weininger.
    “Anytime Guarantees for Reachability in Uncountable Markov Decision Processes.”
    In <i>33rd International Conference on Concurrency Theory </i>, Vol. 243. Schloss
    Dagstuhl - Leibniz-Zentrum für Informatik, 2022. <a href="https://doi.org/10.4230/LIPIcs.CONCUR.2022.11">https://doi.org/10.4230/LIPIcs.CONCUR.2022.11</a>.
  ieee: K. Grover, J. Kretinsky, T. Meggendorfer, and M. Weininger, “Anytime guarantees
    for reachability in uncountable Markov decision processes,” in <i>33rd International
    Conference on Concurrency Theory </i>, Warsaw, Poland, 2022, vol. 243.
  ista: 'Grover K, Kretinsky J, Meggendorfer T, Weininger M. 2022. Anytime guarantees
    for reachability in uncountable Markov decision processes. 33rd International
    Conference on Concurrency Theory . CONCUR: Conference on Concurrency Theory, LIPIcs,
    vol. 243, 11.'
  mla: Grover, Kush, et al. “Anytime Guarantees for Reachability in Uncountable Markov
    Decision Processes.” <i>33rd International Conference on Concurrency Theory </i>,
    vol. 243, 11, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022, doi:<a
    href="https://doi.org/10.4230/LIPIcs.CONCUR.2022.11">10.4230/LIPIcs.CONCUR.2022.11</a>.
  short: K. Grover, J. Kretinsky, T. Meggendorfer, M. Weininger, in:, 33rd International
    Conference on Concurrency Theory , Schloss Dagstuhl - Leibniz-Zentrum für Informatik,
    2022.
conference:
  end_date: 2022-09-16
  location: Warsaw, Poland
  name: 'CONCUR: Conference on Concurrency Theory'
  start_date: 2022-09-13
date_created: 2023-03-28T08:09:32Z
date_published: 2022-09-15T00:00:00Z
date_updated: 2023-09-26T10:43:30Z
day: '15'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.4230/LIPIcs.CONCUR.2022.11
external_id:
  arxiv:
  - '2008.04824'
file:
- access_level: open_access
  checksum: e282e43d3ae0ba6e067b72f4583e13c0
  content_type: application/pdf
  creator: dernst
  date_created: 2023-09-26T10:43:15Z
  date_updated: 2023-09-26T10:43:15Z
  file_id: '14372'
  file_name: 2022_LIPIcS_Grover.pdf
  file_size: 960036
  relation: main_file
  success: 1
file_date_updated: 2023-09-26T10:43:15Z
has_accepted_license: '1'
intvolume: '       243'
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
publication: '33rd International Conference on Concurrency Theory '
publication_identifier:
  issn:
  - 1868-8969
publication_status: published
publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik
quality_controlled: '1'
scopus_import: '1'
status: public
title: Anytime guarantees for reachability in uncountable Markov decision processes
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: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 243
year: '2022'
...
---
_id: '12776'
abstract:
- lang: eng
  text: An improved asymptotic formula is established for the number of rational points
    of bounded height on the split smooth del Pezzo surface of degree 5. The proof
    uses the five conic bundle structures on the surface.
acknowledgement: This work was begun while the author was participating in the programme
  on "Diophantine equations" at the Hausdorff Research Institute for Mathematics in
  Bonn in 2009. The hospitality and financial support of the institute is gratefully
  acknowledged. The idea of using conic bundles to study the split del Pezzo surface
  of degree 5 was explained to the author by Professor Salberger. The author is very
  grateful to him for his input into this project and also to Shuntaro Yamagishi for
  many useful comments on an earlier version of this manuscript. While working on
  this paper the author was supported by FWF grant P32428-N35.
article_processing_charge: No
article_type: original
author:
- first_name: Timothy D
  full_name: Browning, Timothy D
  id: 35827D50-F248-11E8-B48F-1D18A9856A87
  last_name: Browning
  orcid: 0000-0002-8314-0177
citation:
  ama: Browning TD. Revisiting the Manin–Peyre conjecture for the split del Pezzo
    surface of degree 5. <i>New York Journal of Mathematics</i>. 2022;28:1193-1229.
  apa: Browning, T. D. (2022). Revisiting the Manin–Peyre conjecture for the split
    del Pezzo surface of degree 5. <i>New York Journal of Mathematics</i>. State University
    of New York.
  chicago: Browning, Timothy D. “Revisiting the Manin–Peyre Conjecture for the Split
    Del Pezzo Surface of Degree 5.” <i>New York Journal of Mathematics</i>. State
    University of New York, 2022.
  ieee: T. D. Browning, “Revisiting the Manin–Peyre conjecture for the split del Pezzo
    surface of degree 5,” <i>New York Journal of Mathematics</i>, vol. 28. State University
    of New York, pp. 1193–1229, 2022.
  ista: Browning TD. 2022. Revisiting the Manin–Peyre conjecture for the split del
    Pezzo surface of degree 5. New York Journal of Mathematics. 28, 1193–1229.
  mla: Browning, Timothy D. “Revisiting the Manin–Peyre Conjecture for the Split Del
    Pezzo Surface of Degree 5.” <i>New York Journal of Mathematics</i>, vol. 28, State
    University of New York, 2022, pp. 1193–229.
  short: T.D. Browning, New York Journal of Mathematics 28 (2022) 1193–1229.
date_created: 2023-03-28T09:21:09Z
date_published: 2022-08-24T00:00:00Z
date_updated: 2023-10-18T07:59:13Z
day: '24'
ddc:
- '510'
department:
- _id: TiBr
file:
- access_level: open_access
  checksum: c01e8291794a1bdb7416aa103cb68ef8
  content_type: application/pdf
  creator: dernst
  date_created: 2023-03-30T07:09:35Z
  date_updated: 2023-03-30T07:09:35Z
  file_id: '12778'
  file_name: 2022_NYJM_Browning.pdf
  file_size: 897267
  relation: main_file
  success: 1
file_date_updated: 2023-03-30T07:09:35Z
has_accepted_license: '1'
intvolume: '        28'
language:
- iso: eng
month: '08'
oa: 1
oa_version: Published Version
page: 1193 - 1229
project:
- _id: 26AEDAB2-B435-11E9-9278-68D0E5697425
  call_identifier: FWF
  grant_number: P32428
  name: New frontiers of the Manin conjecture
publication: New York Journal of Mathematics
publication_identifier:
  issn:
  - 1076-9803
publication_status: published
publisher: State University of New York
quality_controlled: '1'
status: public
title: Revisiting the Manin–Peyre conjecture for the split del Pezzo surface of degree
  5
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: 28
year: '2022'
...
