@inproceedings{11452, abstract = {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.}, author = {Alimisis, Foivos and Davies, Peter and Vandereycken, Bart and Alistarh, Dan-Adrian}, booktitle = {Advances in Neural Information Processing Systems - 35th Conference on Neural Information Processing Systems}, isbn = {9781713845393}, issn = {1049-5258}, location = {Virtual, Online}, pages = {2823--2834}, publisher = {Neural Information Processing Systems Foundation}, title = {{Distributed principal component analysis with limited communication}}, volume = {4}, year = {2021}, } @inproceedings{11453, abstract = {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, e.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.}, author = {Braun, Lukas and Vogels, Tim P}, booktitle = {Advances in Neural Information Processing Systems - 35th Conference on Neural Information Processing Systems}, isbn = {9781713845393}, issn = {1049-5258}, location = {Virtual, Online}, pages = {16437--16450}, publisher = {Neural Information Processing Systems Foundation}, title = {{Online learning of neural computations from sparse temporal feedback}}, volume = {20}, year = {2021}, } @inproceedings{11458, abstract = {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.}, author = {Peste, Elena-Alexandra and Iofinova, Eugenia B and Vladu, Adrian and Alistarh, Dan-Adrian}, booktitle = {35th Conference on Neural Information Processing Systems}, isbn = {9781713845393}, issn = {1049-5258}, location = {Virtual, Online}, pages = {8557--8570}, publisher = {Curran Associates}, title = {{AC/DC: Alternating Compressed/DeCompressed training of deep neural networks}}, volume = {34}, year = {2021}, } @inproceedings{11463, abstract = {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 or 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 two 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].}, author = {Frantar, Elias and Kurtic, Eldar and Alistarh, Dan-Adrian}, booktitle = {35th Conference on Neural Information Processing Systems}, isbn = {9781713845393}, issn = {1049-5258}, location = {Virtual, Online}, pages = {14873--14886}, publisher = {Curran Associates}, title = {{M-FAC: Efficient matrix-free approximations of second-order information}}, volume = {34}, year = {2021}, } @inproceedings{11464, abstract = {We consider a standard distributed optimisation setting where N machines, each holding a d-dimensional function fi, 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.}, author = {Alistarh, Dan-Adrian and Korhonen, Janne}, booktitle = {35th Conference on Neural Information Processing Systems}, isbn = {9781713845393}, issn = {1049-5258}, location = {Virtual, Online}, pages = {7254--7266}, publisher = {Curran Associates}, title = {{Towards tight communication lower bounds for distributed optimisation}}, volume = {34}, year = {2021}, } @unpublished{12076, abstract = {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.}, author = {Shute, Alec L}, booktitle = {arXiv}, title = {{Sums of four squareful numbers}}, doi = {10.48550/arXiv.2104.06966}, year = {2021}, } @unpublished{12077, abstract = {We compare the Manin-type conjecture for Campana points recently formulated by Pieropan, Smeets, Tanimoto and V\'{a}rilly-Alvarado with an alternative prediction of Browning and Van Valckenborgh in the special case of the orbifold $(\mathbb{P}^1,D)$, 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 could explain this discrepancy. Motivated by this, we provide a counterexample to the Manin-type conjecture for Campana points, by considering orbifolds corresponding to squareful values of binary quadratic forms.}, author = {Shute, Alec L}, booktitle = {arXiv}, title = {{On the leading constant in the Manin-type conjecture for Campana points}}, doi = {10.48550/arXiv.2104.14946}, year = {2021}, } @article{12186, abstract = {Activation of cell-surface and intracellular receptor-mediated immunity results in rapid transcriptional reprogramming that underpins disease resistance. However, the mechanisms by which co-activation of both immune systems lead to transcriptional changes are not clear. Here, we combine RNA-seq and ATAC-seq to define changes in gene expression and chromatin accessibility. Activation of cell-surface or intracellular receptor-mediated immunity, or both, increases chromatin accessibility at induced defence genes. Analysis of ATAC-seq and RNA-seq data combined with publicly available information on transcription factor DNA-binding motifs enabled comparison of individual gene regulatory networks activated by cell-surface or intracellular receptor-mediated immunity, or by both. These results and analyses reveal overlapping and conserved transcriptional regulatory mechanisms between the two immune systems.}, author = {Ding, Pingtao and Sakai, Toshiyuki and Krishna Shrestha, Ram and Manosalva Perez, Nicolas and Guo, Wenbin and Ngou, Bruno Pok Man and He, Shengbo and Liu, Chang and Feng, Xiaoqi and Zhang, Runxuan and Vandepoele, Klaas and MacLean, Dan and Jones, Jonathan D G}, issn = {0022-0957}, journal = {Journal of Experimental Botany}, keywords = {Plant Science, Physiology}, number = {22}, pages = {7927--7941}, publisher = {Oxford University Press}, title = {{Chromatin accessibility landscapes activated by cell-surface and intracellular immune receptors}}, doi = {10.1093/jxb/erab373}, volume = {72}, year = {2021}, } @article{12187, abstract = {Genomes of germ cells present an existential vulnerability to organisms because germ cell mutations will propagate to future generations. Transposable elements are one source of such mutations. In the small flowering plant Arabidopsis, Long et al. found that genome methylation in the male germline is directed by small interfering RNAs (siRNAs) imperfectly transcribed from transposons (see the Perspective by Mosher). These germline siRNAs silence germline transposons and establish inherited methylation patterns in sperm, thus maintaining the integrity of the plant genome across generations.}, author = {Long, Jincheng and Walker, James and She, Wenjing and Aldridge, Billy and Gao, Hongbo and Deans, Samuel and Vickers, Martin and Feng, Xiaoqi}, issn = {0036-8075}, journal = {Science}, keywords = {Multidisciplinary}, number = {6550}, publisher = {American Association for the Advancement of Science (AAAS)}, title = {{Nurse cell--derived small RNAs define paternal epigenetic inheritance in Arabidopsis}}, doi = {10.1126/science.abh0556}, volume = {373}, year = {2021}, } @inproceedings{12767, abstract = {Several problems in planning and reactive synthesis can be reduced to the analysis of two-player quantitative graph games. Optimization is one form of analysis. We argue that in many cases it may be better to replace the optimization problem with the satisficing problem, where instead of searching for optimal solutions, the goal is to search for solutions that adhere to a given threshold bound. This work defines and investigates the satisficing problem on a two-player graph game with the discounted-sum cost model. We show that while the satisficing problem can be solved using numerical methods just like the optimization problem, this approach does not render compelling benefits over optimization. When the discount factor is, however, an integer, we present another approach to satisficing, which is purely based on automata methods. We show that this approach is algorithmically more performant – both theoretically and empirically – and demonstrates the broader applicability of satisficing over optimization.}, author = {Bansal, Suguman and Chatterjee, Krishnendu and Vardi, Moshe Y.}, booktitle = {27th International Conference on Tools and Algorithms for the Construction and Analysis of Systems}, isbn = {9783030720155}, issn = {1611-3349}, location = {Luxembourg City, Luxembourg}, pages = {20--37}, publisher = {Springer Nature}, title = {{On satisficing in quantitative games}}, doi = {10.1007/978-3-030-72016-2}, volume = {12651}, year = {2021}, } @inproceedings{12909, author = {Schlögl, Alois and Elefante, Stefano and Hornoiu, Andrei and Stadlbauer, Stephan}, booktitle = {ASHPC21 – Austrian-Slovenian HPC Meeting 2021}, isbn = {978-961-6980-77-7}, location = {Virtual}, pages = {5}, publisher = {University of Ljubljana}, title = {{Managing software on a heterogenous HPC cluster}}, doi = {10.3359/2021hpc}, year = {2021}, } @misc{12987, abstract = {Chromosomal inversion polymorphisms, segments of chromosomes that are flipped in orientation and occur in reversed order in some individuals, have long been recognized to play an important role in local adaptation. They can reduce recombination in heterozygous individuals and thus help to maintain sets of locally adapted alleles. In a wide range of organisms, populations adapted to different habitats differ in frequency of inversion arrangements. However, getting a full understanding of the importance of inversions for adaptation requires confirmation of their influence on traits under divergent selection. Here, we studied a marine snail, Littorina saxatilis, that has evolved ecotypes adapted to wave exposure or crab predation. These two types occur in close proximity on different parts of the shore. Gene flow between them exists in contact zones. However, they exhibit strong phenotypic divergence in several traits under habitat-specific selection, including size, shape and behaviour. We used crosses between these ecotypes to identify genomic regions that explain variation in these traits by using QTL analysis and variance partitioning across linkage groups. We could show that previously detected inversion regions contribute to adaptive divergence. Some inversions influenced multiple traits suggesting that they contain sets of locally adaptive alleles. Our study also identified regions without known inversions that are important for phenotypic divergence. Thus, we provide a more complete overview of the importance of inversions in relation to the remaining genome.}, author = {Koch, Eva and Morales, Hernán E. and Larsson, Jenny and Westram, Anja M and Faria, Rui and Lemmon, Alan R. and Lemmon, E. Moriarty and Johannesson, Kerstin and Butlin, Roger K.}, publisher = {Dryad}, title = {{Data from: Genetic variation for adaptive traits is associated with polymorphic inversions in Littorina saxatilis}}, doi = {10.5061/DRYAD.ZGMSBCCB4}, year = {2021}, } @misc{13057, abstract = {This dataset comprises all data shown in the figures of the submitted article "Geometric superinductance qubits: Controlling phase delocalization across a single Josephson junction". Additional raw data are available from the corresponding author on reasonable request.}, author = {Peruzzo, Matilda and Hassani, Farid and Szep, Grisha and Trioni, Andrea and Redchenko, Elena and Zemlicka, Martin and Fink, Johannes M}, publisher = {Zenodo}, title = {{Geometric superinductance qubits: Controlling phase delocalization across a single Josephson junction}}, doi = {10.5281/ZENODO.5592103}, year = {2021}, } @misc{13058, abstract = {The zip file includes source data used in the main text of the manuscript "Theory of branching morphogenesis by local interactions and global guidance", as well as a representative Jupyter notebook to reproduce the main figures. A sample script for the simulations of branching and annihilating random walks is also included (Sample_script_for_simulations_of_BARWs.ipynb) to generate exemplary branched networks under external guidance. A detailed description of the simulation setup is provided in the supplementary information of the manuscipt.}, author = {Ucar, Mehmet C}, publisher = {Zenodo}, title = {{Source data for the manuscript "Theory of branching morphogenesis by local interactions and global guidance"}}, doi = {10.5281/ZENODO.5257160}, year = {2021}, } @misc{13061, abstract = {Infections early in life can have enduring effects on an organism’s development and immunity. In this study, we show that this equally applies to developing “superorganisms” – incipient social insect colonies. When we exposed newly mated Lasius niger ant queens to a low pathogen dose, their colonies grew more slowly than controls before winter, but reached similar sizes afterwards. Independent of exposure, queen hibernation survival improved when the ratio of pupae to workers was small. Queens that reared fewer pupae before worker emergence exhibited lower pathogen levels, indicating that high brood rearing efforts interfere with the ability of the queen’s immune system to suppress pathogen proliferation. Early-life queen pathogen-exposure also improved the immunocompetence of her worker offspring, as demonstrated by challenging the workers to the same pathogen a year later. Transgenerational transfer of the queen’s pathogen experience to her workforce can hence durably reduce the disease susceptibility of the whole superorganism.}, author = {Casillas Perez, Barbara E and Pull, Christopher and Naiser, Filip and Naderlinger, Elisabeth and Matas, Jiri and Cremer, Sylvia}, publisher = {Dryad}, title = {{Early queen infection shapes developmental dynamics and induces long-term disease protection in incipient ant colonies}}, doi = {10.5061/DRYAD.7PVMCVDTJ}, year = {2021}, } @misc{13062, abstract = {This paper analyzes the conditions for local adaptation in a metapopulation with infinitely many islands under a model of hard selection, where population size depends on local fitness. Each island belongs to one of two distinct ecological niches or habitats. Fitness is influenced by an additive trait which is under habitat-dependent directional selection. Our analysis is based on the diffusion approximation and accounts for both genetic drift and demographic stochasticity. By neglecting linkage disequilibria, it yields the joint distribution of allele frequencies and population size on each island. We find that under hard selection, the conditions for local adaptation in a rare habitat are more restrictive for more polygenic traits: even moderate migration load per locus at very many loci is sufficient for population sizes to decline. This further reduces the efficacy of selection at individual loci due to increased drift and because smaller populations are more prone to swamping due to migration, causing a positive feedback between increasing maladaptation and declining population sizes. Our analysis also highlights the importance of demographic stochasticity, which exacerbates the decline in numbers of maladapted populations, leading to population collapse in the rare habitat at significantly lower migration than predicted by deterministic arguments.}, author = {Szep, Eniko and Sachdeva, Himani and Barton, Nicholas H}, publisher = {Dryad}, title = {{Supplementary code for: Polygenic local adaptation in metapopulations: A stochastic eco-evolutionary model}}, doi = {10.5061/DRYAD.8GTHT76P1}, year = {2021}, } @misc{13063, abstract = {We develop a Bayesian model (BayesRR-RC) that provides robust SNP-heritability estimation, an alternative to marker discovery, and accurate genomic prediction, taking 22 seconds per iteration to estimate 8.4 million SNP-effects and 78 SNP-heritability parameters in the UK Biobank. We find that only $\leq$ 10\% of the genetic variation captured for height, body mass index, cardiovascular disease, and type 2 diabetes is attributable to proximal regulatory regions within 10kb upstream of genes, while 12-25% is attributed to coding regions, 32-44% to introns, and 22-28% to distal 10-500kb upstream regions. Up to 24% of all cis and coding regions of each chromosome are associated with each trait, with over 3,100 independent exonic and intronic regions and over 5,400 independent regulatory regions having >95% probability of contributing >0.001% to the genetic variance of these four traits. Our open-source software (GMRM) provides a scalable alternative to current approaches for biobank data.}, author = {Robinson, Matthew Richard}, publisher = {Dryad}, title = {{Probabilistic inference of the genetic architecture of functional enrichment of complex traits}}, doi = {10.5061/dryad.sqv9s4n51}, year = {2021}, } @misc{13068, abstract = {Source data and source code for the graphs in "Spatiotemporal dynamics of self-organized branching pancreatic cancer-derived organoids".}, author = {Randriamanantsoa, Samuel and Papargyriou, Aristeidis and Maurer, Carlo and Peschke, Katja and Schuster, Maximilian and Zecchin, Giulia and Steiger, Katja and Öllinger, Rupert and Saur, Dieter and Scheel, Christina and Rad, Roland and Hannezo, Edouard B and Reichert, Maximilian and Bausch, Andreas R.}, publisher = {Zenodo}, title = {{Spatiotemporal dynamics of self-organized branching in pancreas-derived organoids}}, doi = {10.5281/ZENODO.5148117}, year = {2021}, } @misc{13069, abstract = {To survive elevated temperatures, ectotherms adjust the fluidity of membranes by fine-tuning lipid desaturation levels in a process previously described to be cell-autonomous. We have discovered that, in Caenorhabditis elegans, neuronal Heat shock Factor 1 (HSF-1), the conserved master regulator of the heat shock response (HSR)- causes extensive fat remodelling in peripheral tissues. These changes include a decrease in fat desaturase and acid lipase expression in the intestine, and a global shift in the saturation levels of plasma membrane’s phospholipids. The observed remodelling of plasma membrane is in line with ectothermic adaptive responses and gives worms a cumulative advantage to warm temperatures. We have determined that at least six TAX-2/TAX-4 cGMP gated channel expressing sensory neurons and TGF-β/BMP are required for signalling across tissues to modulate fat desaturation. We also find neuronal hsf-1 is not only sufficient but also partially necessary to control the fat remodelling response and for survival at warm temperatures. This is the first study to show that a thermostat-based mechanism can cell non-autonomously coordinate membrane saturation and composition across tissues in a multicellular animal.}, author = {Chauve, Laetitia and Hodge, Francesca and Murdoch, Sharlene and Masoudzadeh, Fatemah and Mann, Harry-Jack and Lopez-Clavijo, Andrea and Okkenhaug, Hanneke and West, Greg and Sousa, Bebiana C. and Segonds-Pichon, Anne and Li, Cheryl and Wingett, Steven and Kienberger, Hermine and Kleigrewe, Karin and de Bono, Mario and Wakelam, Michael and Casanueva, Olivia}, publisher = {Zenodo}, title = {{Neuronal HSF-1 coordinates the propagation of fat desaturation across tissues to enable adaptation to high temperatures in C. elegans}}, doi = {10.5281/ZENODO.5519410}, year = {2021}, } @misc{13072, abstract = {CpGs and corresponding mean weights for DNAm-based prediction of cognitive abilities (6 traits)}, author = {McCartney, Daniel L and Hillary, Robert F and Conole, Eleanor LS and Trejo Banos, Daniel and Gadd, Danni A and Walker, Rosie M and Nangle, Cliff and Flaig, Robin and Campbell, Archie and Murray, Alison D and Munoz Maniega, Susana and del C Valdes-Hernandez, Maria and Harris, Mathew A and Bastin, Mark E and Wardlaw, Joanna M and Harris, Sarah E and Porteous, David J and Tucker-Drob, Elliot M and McIntosh, Andrew M and Evans, Kathryn L and Deary, Ian J and Cox, Simon R and Robinson, Matthew Richard and Marioni, Riccardo E}, publisher = {Zenodo}, title = {{Blood-based epigenome-wide analyses of cognitive abilities}}, doi = {10.5281/ZENODO.5794028}, year = {2021}, }