{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/open-question/papers/6","list_of":"/task/open-question","task":"Open-Ended Question Answering","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":6,"pages_in_order":8,"rows_per_page":100,"rows":[501,600],"of":796,"counts":{"archive_papers_tagged":796,"with_a_code_link":228,"where_syntology_ran_a_sample":70,"not_listed_spam_title":0,"listed":796,"listed_where_code_ran":70,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":59,"every_run_a_failure_of_syntologys_instrument":11,"listed_with_a_run_with_no_instrument_failure":59,"listed_every_run_a_failure_of_syntologys_instrument":11,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/open-question","prev":"/task/open-question/papers/5","next":"/task/open-question/papers/7","papers":[{"url":null,"slug":"net-dnf-effective-deep-modeling-of-tabular","title":"Net-DNF: Effective Deep Modeling of Tabular Data","date":"2021-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-marginal-regret-bound-minimization-of","title":"On the Marginal Regret Bound Minimization of Adaptive Methods","date":"2021-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"thda-treasure-hunt-data-augmentation-for","title":"THDA: Treasure Hunt Data Augmentation for Semantic Navigation","date":"2021-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"growth-development-and-structural-change-at","title":"Growth, development, and structural change at the firm-level: The example of the PR China","date":"2020-12-28","arxiv_id":"2012.14503","repositories_listed":0,"syntology":null},{"url":null,"slug":"is-fft-fast-enough-for-beyond-5g","title":"Is FFT Fast Enough for Beyond-5G Communications?","date":"2020-12-14","arxiv_id":"2012.07497","repositories_listed":0,"syntology":null},{"url":null,"slug":"streaming-algorithms-for-stochastic-multi","title":"Streaming Algorithms for Stochastic Multi-armed Bandits","date":"2020-12-09","arxiv_id":"2012.05142","repositories_listed":0,"syntology":null},{"url":null,"slug":"designing-templates-for-eliciting-commonsense","title":"Designing Templates for Eliciting Commonsense Knowledge from Pretrained Sequence-to-Sequence Models","date":"2020-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"profile-prediction-an-alignment-based-pre","title":"Profile Prediction: An Alignment-Based Pre-Training Task for Protein Sequence Models","date":"2020-12-01","arxiv_id":"2012.00195","repositories_listed":0,"syntology":null},{"url":null,"slug":"predicting-prostate-cancer-specific-mortality","title":"Predicting Prostate Cancer-Specific Mortality with A.I.-based Gleason Grading","date":"2020-11-25","arxiv_id":"2012.05197","repositories_listed":0,"syntology":null},{"url":null,"slug":"experiments-on-transfer-learning","title":"Experiments on transfer learning architectures for biomedical relation extraction","date":"2020-11-24","arxiv_id":"2011.12380","repositories_listed":0,"syntology":null},{"url":null,"slug":"2cp-decentralized-protocols-to-transparently","title":"2CP: Decentralized Protocols to Transparently Evaluate Contributivity in Blockchain Federated Learning Environments","date":"2020-11-15","arxiv_id":"2011.07516","repositories_listed":0,"syntology":null},{"url":null,"slug":"fluctuation-spectra-of-large-random-dynamical","title":"Fluctuation spectra of large random dynamical systems reveal hidden structure in ecological networks","date":"2020-11-10","arxiv_id":"2011.05140","repositories_listed":0,"syntology":null},{"url":null,"slug":"how-much-over-parameterization-is-sufficient-1","title":"How Much Over-parameterization Is Sufficient to Learn Deep ReLU Networks?","date":"2020-10-23","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"do-deeper-convolutional-networks-perform-1","title":"Increasing Depth Leads to U-Shaped Test Risk in Over-parameterized Convolutional Networks","date":"2020-10-19","arxiv_id":"2010.09610","repositories_listed":0,"syntology":null},{"url":null,"slug":"cluster-activation-mapping-with-applications","title":"Cluster Activation Mapping with Applications to Medical Imaging","date":"2020-10-09","arxiv_id":"2010.04794","repositories_listed":0,"syntology":null},{"url":null,"slug":"duff-a-dataset-distance-based-utility","title":"Duff: A Dataset-Distance-Based Utility Function Family for the Exponential Mechanism","date":"2020-10-08","arxiv_id":"2010.04235","repositories_listed":0,"syntology":null},{"url":null,"slug":"can-you-trust-your-pose-confidence-estimation","title":"Can You Trust Your Pose? Confidence Estimation in Visual Localization","date":"2020-10-01","arxiv_id":"2010.00347","repositories_listed":0,"syntology":null},{"url":null,"slug":"transfer-among-agents-an-efficient-multiagent","title":"Transfer among Agents: An Efficient Multiagent Transfer Learning Framework","date":"2020-09-28","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"influence-of-segmentation-accuracy-in","title":"Influence of segmentation accuracy in structural MR head scans on electric field computation for TMS and tES","date":"2020-09-25","arxiv_id":"2009.12015","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-distributed-differential-privacy-and","title":"On Distributed Differential Privacy and Counting Distinct Elements","date":"2020-09-21","arxiv_id":"2009.09604","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-next-era-of-american-law-amid-the-advent","title":"The Next Era of American Law Amid the Advent of Autonomous AI Legal Reasoning","date":"2020-09-21","arxiv_id":"2009.11647","repositories_listed":0,"syntology":null},{"url":null,"slug":"skeletonization-and-reconstruction-based-on","title":"Skeletonization and Reconstruction based on Graph Morphological Transformations","date":"2020-09-16","arxiv_id":"2009.07970","repositories_listed":0,"syntology":null},{"url":null,"slug":"detecting-and-adapting-to-crisis-pattern-with","title":"Detecting and adapting to crisis pattern with context based Deep Reinforcement Learning","date":"2020-09-07","arxiv_id":"2009.07200","repositories_listed":0,"syntology":null},{"url":null,"slug":"scg-net-self-constructing-graph-neural","title":"SCG-Net: Self-Constructing Graph Neural Networks for Semantic Segmentation","date":"2020-09-03","arxiv_id":"2009.01599","repositories_listed":0,"syntology":null},{"url":null,"slug":"selective-particle-attention-visual-feature","title":"Selective Particle Attention: Visual Feature-Based Attention in Deep Reinforcement Learning","date":"2020-08-26","arxiv_id":"2008.11491","repositories_listed":0,"syntology":null},{"url":null,"slug":"robust-reinforcement-learning-a-case-study-in","title":"Robust Reinforcement Learning: A Case Study in Linear Quadratic Regulation","date":"2020-08-25","arxiv_id":"2008.11592","repositories_listed":0,"syntology":null},{"url":null,"slug":"raf-au-database-in-the-wild-facial","title":"RAF-AU Database: In-the-Wild Facial Expressions with Subjective Emotion Judgement and Objective AU Annotations","date":"2020-08-12","arxiv_id":"2008.05196","repositories_listed":0,"syntology":null},{"url":null,"slug":"efficient-integration-of-multi-channel","title":"Efficient Integration of Multi-channel Information for Speaker-independent Speech Separation","date":"2020-08-11","arxiv_id":"2005.11612","repositories_listed":0,"syntology":null},{"url":null,"slug":"transferring-inter-class-correlation","title":"Transferring Inter-Class Correlation","date":"2020-08-11","arxiv_id":"2008.10444","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantum-versus-classical-generative-modelling","title":"Quantum versus Classical Generative Modelling in Finance","date":"2020-08-03","arxiv_id":"2008.00691","repositories_listed":0,"syntology":null},{"url":null,"slug":"universal-approximation-with-neural-intensity","title":"UNIPoint: Universally Approximating Point Processes Intensities","date":"2020-07-28","arxiv_id":"2007.14082","repositories_listed":0,"syntology":null},{"url":null,"slug":"characterizing-the-effect-of-sentence-context","title":"Characterizing the Effect of Sentence Context on Word Meanings: Mapping Brain to Behavior","date":"2020-07-27","arxiv_id":"2007.13840","repositories_listed":0,"syntology":null},{"url":null,"slug":"approximately-optimal-binning-for-the","title":"Approximately Optimal Binning for the Piecewise Constant Approximation of the Normalized Unexplained Variance (nUV) Dissimilarity Measure","date":"2020-07-24","arxiv_id":"2007.12463","repositories_listed":0,"syntology":null},{"url":null,"slug":"mi-2gan-generative-adversarial-network-for","title":"MI^2GAN: Generative Adversarial Network for Medical Image Domain Adaptation using Mutual Information Constraint","date":"2020-07-22","arxiv_id":"2007.11180","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-convergence-of-reinforcement-learning","title":"On the Convergence of Reinforcement Learning with Monte Carlo Exploring Starts","date":"2020-07-21","arxiv_id":"2007.10916","repositories_listed":0,"syntology":null},{"url":null,"slug":"learn-to-propagate-reliably-on-noisy-affinity","title":"Learn to Propagate Reliably on Noisy Affinity Graphs","date":"2020-07-17","arxiv_id":"2007.08802","repositories_listed":0,"syntology":null},{"url":null,"slug":"how-retroactivity-affects-the-behavior-of","title":"How Retroactivity Affects the Behavior of Incoherent Feed-Forward Loops","date":"2020-07-15","arxiv_id":"2007.07737","repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-distillation-beyond-model","title":"Knowledge Distillation Beyond Model Compression","date":"2020-07-03","arxiv_id":"2007.01922","repositories_listed":0,"syntology":null},{"url":null,"slug":"compositionality-and-capacity-in-emergent","title":"Compositionality and Capacity in Emergent Languages","date":"2020-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"robust-linear-regression-optimal-rates-in","title":"Robust Linear Regression: Optimal Rates in Polynomial Time","date":"2020-06-29","arxiv_id":"2007.01394","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-tuning-of-stochastic-gradient","title":"Automatic Tuning of Stochastic Gradient Descent with Bayesian Optimisation","date":"2020-06-25","arxiv_id":"2006.14376","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-empirical-neural-tangent-kernel-of","title":"On the Empirical Neural Tangent Kernel of Standard Finite-Width Convolutional Neural Network Architectures","date":"2020-06-24","arxiv_id":"2006.13645","repositories_listed":0,"syntology":null},{"url":null,"slug":"algorithms-and-sq-lower-bounds-for-pac","title":"Algorithms and SQ Lower Bounds for PAC Learning One-Hidden-Layer ReLU Networks","date":"2020-06-22","arxiv_id":"2006.12476","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-divergence-of-decentralized-non-convex","title":"On the Divergence of Decentralized Non-Convex Optimization","date":"2020-06-20","arxiv_id":"2006.11662","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-sparsity-in-overparametrised-shallow-relu","title":"On Sparsity in Overparametrised Shallow ReLU Networks","date":"2020-06-18","arxiv_id":"2006.10225","repositories_listed":0,"syntology":null},{"url":null,"slug":"fourier-sparse-leverage-scores-and","title":"Fourier Sparse Leverage Scores and Approximate Kernel Learning","date":"2020-06-12","arxiv_id":"2006.07340","repositories_listed":0,"syntology":null},{"url":null,"slug":"dnf-net-a-neural-architecture-for-tabular","title":"DNF-Net: A Neural Architecture for Tabular Data","date":"2020-06-11","arxiv_id":"2006.06465","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-strength-of-nesterov-s-extrapolation-in","title":"The Strength of Nesterov's Extrapolation in the Individual Convergence of Nonsmooth Optimization","date":"2020-06-08","arxiv_id":"2006.04340","repositories_listed":0,"syntology":null},{"url":null,"slug":"attribute-efficient-learning-of-halfspaces","title":"Attribute-Efficient Learning of Halfspaces with Malicious Noise: Near-Optimal Label Complexity and Noise Tolerance","date":"2020-06-06","arxiv_id":"2006.03781","repositories_listed":0,"syntology":null},{"url":null,"slug":"would-you-like-to-hear-the-news-investigating","title":"Would You Like to Hear the News? Investigating Voice-BasedSuggestions for Conversational News Recommendation","date":"2020-06-02","arxiv_id":"2006.01926","repositories_listed":0,"syntology":null},{"url":null,"slug":"domain-adaptive-image-to-image-translation","title":"Domain Adaptive Image-to-Image Translation","date":"2020-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-networks-with-small-weights-and-depth","title":"Neural Networks with Small Weights and Depth-Separation Barriers","date":"2020-05-31","arxiv_id":"2006.00625","repositories_listed":0,"syntology":null},{"url":null,"slug":"generalizing-random-fourier-features-via","title":"Fast Learning in Reproducing Kernel Krein Spaces via Signed Measures","date":"2020-05-30","arxiv_id":"2006.00247","repositories_listed":0,"syntology":null},{"url":null,"slug":"syntactic-structure-distillation-pretraining","title":"Syntactic Structure Distillation Pretraining For Bidirectional Encoders","date":"2020-05-27","arxiv_id":"2005.13482","repositories_listed":0,"syntology":null},{"url":null,"slug":"mathematical-analysis-and-potential","title":"Mathematical analysis and potential therapeutic implications of a novel HIV-1 model of basal and activated transcription in T-cells and macrophages","date":"2020-05-22","arxiv_id":"2005.11343","repositories_listed":0,"syntology":null},{"url":null,"slug":"continuous-lwe","title":"Continuous LWE","date":"2020-05-19","arxiv_id":"2005.09595","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-re-examination-of-the-evidence-used-by","title":"A Re-Examination of the Evidence used by Hooge et al (2018) \"Is human classification by experienced untrained observers a gold standard in fixation detection?\"","date":"2020-05-13","arxiv_id":"2001.07701","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-global-convergence-rates-of-softmax","title":"On the Global Convergence Rates of Softmax Policy Gradient Methods","date":"2020-05-13","arxiv_id":"2005.06392","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-comparison-of-explicit-and-implicit","title":"A Comparison of Explicit and Implicit Proactive Dialogue Strategies for Conversational Recommendation","date":"2020-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"rotation-invariant-clustering-of-neuronal","title":"Rotation-invariant clustering of neuronal responses in primary visual cortex","date":"2020-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"an-exposition-to-the-finiteness-of-fibers-in","title":"Low-rank matrix completion theory via Plucker coordinates","date":"2020-04-26","arxiv_id":"2004.12430","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-and-testing-junta-distributions-with","title":"Learning and Testing Junta Distributions with Subcube Conditioning","date":"2020-04-26","arxiv_id":"2004.12496","repositories_listed":0,"syntology":null},{"url":null,"slug":"designing-a-nisq-reservoir-with-maximal","title":"Characterizing the memory capacity of transmon qubit reservoirs","date":"2020-04-15","arxiv_id":"2004.08240","repositories_listed":0,"syntology":null},{"url":null,"slug":"scalable-autonomous-vehicle-safety-validation","title":"Scalable Autonomous Vehicle Safety Validation through Dynamic Programming and Scene Decomposition","date":"2020-04-14","arxiv_id":"2004.06801","repositories_listed":0,"syntology":null},{"url":null,"slug":"stopping-criteria-for-and-strong-convergence","title":"Stopping Criteria for, and Strong Convergence of, Stochastic Gradient Descent on Bottou-Curtis-Nocedal Functions","date":"2020-04-01","arxiv_id":"2004.00475","repositories_listed":0,"syntology":null},{"url":"/paper/weakly-supervised-3d-hand-pose-estimation-via","slug":"weakly-supervised-3d-hand-pose-estimation-via","title":"Weakly Supervised 3D Hand Pose Estimation via Biomechanical Constraints","date":"2020-03-20","arxiv_id":"2003.09282","repositories_listed":0,"syntology":null},{"url":null,"slug":"selectivity-considered-harmful-evaluating-the","title":"Selectivity considered harmful: evaluating the causal impact of class selectivity in DNNs","date":"2020-03-03","arxiv_id":"2003.01262","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-equivalence-between-private-classification","title":"An Equivalence Between Private Classification and Online Prediction","date":"2020-03-01","arxiv_id":"2003.00563","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-spectral-underpinning-of-word2vec","title":"The Spectral Underpinning of word2vec","date":"2020-02-27","arxiv_id":"2002.12317","repositories_listed":0,"syntology":null},{"url":null,"slug":"coherent-gradients-an-approach-to-1","title":"Coherent Gradients: An Approach to Understanding Generalization in Gradient Descent-based Optimization","date":"2020-02-25","arxiv_id":"2002.10657","repositories_listed":0,"syntology":null},{"url":null,"slug":"network-density-controlled-decentralized","title":"Network-Density-Controlled Decentralized Parallel Stochastic Gradient Descent in Wireless Systems","date":"2020-02-25","arxiv_id":"2002.10758","repositories_listed":0,"syntology":null},{"url":null,"slug":"scalable-multi-agent-inverse-reinforcement","title":"Scalable Multi-Agent Inverse Reinforcement Learning via Actor-Attention-Critic","date":"2020-02-24","arxiv_id":"2002.10525","repositories_listed":0,"syntology":null},{"url":null,"slug":"optimal-signal-adaptive-trading-with","title":"Optimal Signal-Adaptive Trading with Temporary and Transient Price Impact","date":"2020-02-21","arxiv_id":"2002.09549","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-halfspaces-with-massart-noise-under","title":"Learning Halfspaces with Massart Noise Under Structured Distributions","date":"2020-02-13","arxiv_id":"2002.05632","repositories_listed":0,"syntology":null},{"url":null,"slug":"metric-free-individual-fairness-in-online","title":"Metric-Free Individual Fairness in Online Learning","date":"2020-02-13","arxiv_id":"2002.05474","repositories_listed":0,"syntology":null},{"url":null,"slug":"revisiting-fixed-support-wasserstein","title":"Fixed-Support Wasserstein Barycenters: Computational Hardness and Fast Algorithm","date":"2020-02-12","arxiv_id":"2002.04783","repositories_listed":0,"syntology":null},{"url":null,"slug":"deepfakes-for-medical-video-de-identification","title":"Deepfakes for Medical Video De-Identification: Privacy Protection and Diagnostic Information Preservation","date":"2020-02-07","arxiv_id":"2003.00813","repositories_listed":0,"syntology":null},{"url":null,"slug":"near-optimal-algorithms-for-minimax","title":"Near-Optimal Algorithms for Minimax Optimization","date":"2020-02-05","arxiv_id":"2002.02417","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-functions-varying-along-an-active","title":"Learning functions varying along a central subspace","date":"2020-01-22","arxiv_id":"2001.07883","repositories_listed":0,"syntology":null},{"url":null,"slug":"memory-capacity-of-neural-networks-with","title":"Memory capacity of neural networks with threshold and ReLU activations","date":"2020-01-20","arxiv_id":"2001.06938","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-bayesian-monte-carlo-uncertainty-model-for","title":"A Bayesian Monte-Carlo Uncertainty Model for Assessment of Shear Stress Entropy","date":"2020-01-10","arxiv_id":"2001.04802","repositories_listed":0,"syntology":null},{"url":null,"slug":"questioning-the-ai-informing-design-practices","title":"Questioning the AI: Informing Design Practices for Explainable AI User Experiences","date":"2020-01-08","arxiv_id":"2001.02478","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-general-recurrent-state-space-framework-for","title":"A general recurrent state space framework for modeling neural dynamics during decision-making","date":"2020-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"erase-and-restore-simple-accurate-and","title":"Exploiting the Sensitivity of $L_2$ Adversarial Examples to Erase-and-Restore","date":"2020-01-01","arxiv_id":"2001.00116","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-in-tractability-of-computing","title":"On the (In)tractability of Computing Normalizing Constants for the Product of Determinantal Point Processes","date":"2020-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-from-learning-machines-optimisation","title":"Learning from Learning Machines: Optimisation, Rules, and Social Norms","date":"2019-12-29","arxiv_id":"2001.00006","repositories_listed":0,"syntology":null},{"url":null,"slug":"depth-width-trade-offs-for-relu-networks-via-1","title":"Depth-Width Trade-offs for ReLU Networks via Sharkovsky's Theorem","date":"2019-12-09","arxiv_id":"1912.04378","repositories_listed":0,"syntology":null},{"url":null,"slug":"noisy-greedy-and-not-so-greedy-k-means","title":"Noisy, Greedy and Not So Greedy k-means++","date":"2019-12-02","arxiv_id":"1912.00653","repositories_listed":0,"syntology":null},{"url":null,"slug":"sample-complexity-of-learning-mixture-of","title":"Sample Complexity of Learning Mixture of Sparse Linear Regressions","date":"2019-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-reparameterization-invariant-flatness","title":"A Reparameterization-Invariant Flatness Measure for Deep Neural Networks","date":"2019-11-29","arxiv_id":"1912.00058","repositories_listed":0,"syntology":null},{"url":null,"slug":"how-much-over-parameterization-is-sufficient","title":"How Much Over-parameterization Is Sufficient to Learn Deep ReLU Networks?","date":"2019-11-27","arxiv_id":"1911.12360","repositories_listed":0,"syntology":null},{"url":null,"slug":"all-pay-bidding-games-on-graphs","title":"All-Pay Bidding Games on Graphs","date":"2019-11-19","arxiv_id":"1911.08360","repositories_listed":0,"syntology":null},{"url":null,"slug":"information-theoretic-perspective-of","title":"Information-Theoretic Perspective of Federated Learning","date":"2019-11-15","arxiv_id":"1911.07652","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-comparison-of-end-to-end-models-for-long","title":"A comparison of end-to-end models for long-form speech recognition","date":"2019-11-06","arxiv_id":"1911.02242","repositories_listed":0,"syntology":null},{"url":null,"slug":"relative-maximum-likelihood-updating-of","title":"Relative Maximum Likelihood Updating of Ambiguous Beliefs","date":"2019-11-06","arxiv_id":"1911.02678","repositories_listed":0,"syntology":null},{"url":null,"slug":"sample-complexity-of-learning-mixtures-of","title":"Sample Complexity of Learning Mixtures of Sparse Linear Regressions","date":"2019-10-30","arxiv_id":"1910.14106","repositories_listed":0,"syntology":null},{"url":null,"slug":"hyperbolic-node-embedding-for-signed-networks","title":"Hyperbolic Node Embedding for Signed Networks","date":"2019-10-29","arxiv_id":"1910.13090","repositories_listed":0,"syntology":null},{"url":null,"slug":"intelligence-via-ultrafilters-structural","title":"Intelligence via ultrafilters: structural properties of some intelligence comparators of deterministic Legg-Hutter agents","date":"2019-10-22","arxiv_id":"1910.09721","repositories_listed":0,"syntology":null},{"url":null,"slug":"hv-block-cross-validation-is-not-a-bibd-a","title":"$hv$-Block Cross Validation is not a BIBD: a Note on the Paper by Jeff Racine (2000)","date":"2019-10-20","arxiv_id":"1910.08904","repositories_listed":0,"syntology":null},{"url":null,"slug":"active-learning-for-graph-neural-networks-via","title":"Active Learning for Graph Neural Networks via Node Feature Propagation","date":"2019-10-16","arxiv_id":"1910.07567","repositories_listed":0,"syntology":null}],"record_sha256":"55dedbfde6cfbea6cbf079c14f08514a67e6a9f7883275406e55c4cbc04e2ad8","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}