{"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/generalization-bounds/papers/4","list_of":"/task/generalization-bounds","task":"Generalization Bounds","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":4,"pages_in_order":7,"rows_per_page":100,"rows":[301,400],"of":686,"counts":{"archive_papers_tagged":686,"with_a_code_link":161,"where_syntology_ran_a_sample":55,"not_listed_spam_title":0,"listed":686,"listed_where_code_ran":55,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":45,"every_run_a_failure_of_syntologys_instrument":10,"listed_with_a_run_with_no_instrument_failure":45,"listed_every_run_a_failure_of_syntologys_instrument":10,"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/generalization-bounds","prev":"/task/generalization-bounds/papers/3","next":"/task/generalization-bounds/papers/5","papers":[{"url":null,"slug":"fast-convergence-in-learning-two-layer-neural","title":"Fast Convergence in Learning Two-Layer Neural Networks with Separable Data","date":"2023-05-22","arxiv_id":"2305.13471","repositories_listed":0,"syntology":null},{"url":null,"slug":"uniform-in-time-wasserstein-stability-bounds","title":"Uniform-in-Time Wasserstein Stability Bounds for (Noisy) Stochastic Gradient Descent","date":"2023-05-20","arxiv_id":"2305.12056","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-unified-framework-for-information-theoretic","title":"A unified framework for information-theoretic generalization bounds","date":"2023-05-18","arxiv_id":"2305.11042","repositories_listed":0,"syntology":null},{"url":null,"slug":"generalization-bounds-for-neural-belief","title":"Generalization Bounds for Neural Belief Propagation Decoders","date":"2023-05-17","arxiv_id":"2305.10540","repositories_listed":0,"syntology":null},{"url":null,"slug":"reinterpreting-causal-discovery-as-the-task","title":"Reinterpreting causal discovery as the task of predicting unobserved joint statistics","date":"2023-05-11","arxiv_id":"2305.06894","repositories_listed":0,"syntology":null},{"url":null,"slug":"reweighted-mixup-for-subpopulation-shift","title":"Reweighted Mixup for Subpopulation Shift","date":"2023-04-09","arxiv_id":"2304.04148","repositories_listed":0,"syntology":null},{"url":null,"slug":"infinite-dimensional-reservoir-computing","title":"Infinite-dimensional reservoir computing","date":"2023-04-02","arxiv_id":"2304.00490","repositories_listed":0,"syntology":null},{"url":null,"slug":"lower-generalization-bounds-for-gd-and-sgd-in","title":"Lower Generalization Bounds for GD and SGD in Smooth Stochastic Convex Optimization","date":"2023-03-19","arxiv_id":"2303.10758","repositories_listed":0,"syntology":null},{"url":null,"slug":"fair-off-policy-learning-from-observational","title":"Fair Off-Policy Learning from Observational Data","date":"2023-03-15","arxiv_id":"2303.08516","repositories_listed":0,"syntology":null},{"url":null,"slug":"practicality-of-generalization-guarantees-for","title":"Practicality of generalization guarantees for unsupervised domain adaptation with neural networks","date":"2023-03-15","arxiv_id":"2303.08720","repositories_listed":0,"syntology":null},{"url":null,"slug":"partial-neural-optimal-transport","title":"Light Unbalanced Optimal Transport","date":"2023-03-14","arxiv_id":"2303.07988","repositories_listed":0,"syntology":null},{"url":null,"slug":"data-dependent-generalization-bounds-via","title":"Data-dependent Generalization Bounds via Variable-Size Compressibility","date":"2023-03-09","arxiv_id":"2303.05369","repositories_listed":0,"syntology":null},{"url":null,"slug":"provable-pathways-learning-multiple-tasks","title":"Provable Pathways: Learning Multiple Tasks over Multiple Paths","date":"2023-03-08","arxiv_id":"2303.04338","repositories_listed":0,"syntology":null},{"url":null,"slug":"asymptotically-optimal-generalization-error","title":"Generalization Error Bounds for Noisy, Iterative Algorithms via Maximal Leakage","date":"2023-02-28","arxiv_id":"2302.14518","repositories_listed":0,"syntology":null},{"url":null,"slug":"generalization-bounds-for-set-to-set-matching","title":"Generalization Bounds for Set-to-Set Matching with Negative Sampling","date":"2023-02-25","arxiv_id":"2302.12991","repositories_listed":0,"syntology":null},{"url":null,"slug":"generalization-analysis-for-contrastive","title":"Generalization Analysis for Contrastive Representation Learning","date":"2023-02-24","arxiv_id":"2302.12383","repositories_listed":0,"syntology":null},{"url":null,"slug":"generalization-bounds-for-adversarial","title":"Generalization Bounds for Adversarial Contrastive Learning","date":"2023-02-21","arxiv_id":"2302.10633","repositories_listed":0,"syntology":null},{"url":null,"slug":"stability-based-generalization-analysis-for","title":"Stability-based Generalization Analysis for Mixtures of Pointwise and Pairwise Learning","date":"2023-02-20","arxiv_id":"2302.09967","repositories_listed":0,"syntology":null},{"url":null,"slug":"information-theoretic-lower-bounds-for-4","title":"Information Theoretic Lower Bounds for Information Theoretic Upper Bounds","date":"2023-02-09","arxiv_id":"2302.04925","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-unified-recipe-for-deriving-time-uniform","title":"A unified recipe for deriving (time-uniform) PAC-Bayes bounds","date":"2023-02-07","arxiv_id":"2302.03421","repositories_listed":0,"syntology":null},{"url":null,"slug":"norm-based-generalization-bounds-for","title":"Norm-based Generalization Bounds for Compositionally Sparse Neural Networks","date":"2023-01-28","arxiv_id":"2301.12033","repositories_listed":0,"syntology":null},{"url":null,"slug":"algorithmic-stability-of-heavy-tailed-sgd","title":"Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions","date":"2023-01-27","arxiv_id":"2301.11885","repositories_listed":0,"syntology":null},{"url":"/paper/separate-and-diffuse-using-a-pretrained","slug":"separate-and-diffuse-using-a-pretrained","title":"Separate And Diffuse: Using a Pretrained Diffusion Model for Improving Source Separation","date":"2023-01-25","arxiv_id":"2301.10752","repositories_listed":0,"syntology":null},{"url":null,"slug":"how-to-prevent-the-poor-performance-clients","title":"How To Prevent the Poor Performance Clients for Personalized Federated Learning?","date":"2023-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"leveraging-inter-rater-agreement-for","title":"Leveraging Inter-Rater Agreement for Classification in the Presence of Noisy Labels","date":"2023-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"limitations-of-information-theoretic","title":"Limitations of Information-Theoretic Generalization Bounds for Gradient Descent Methods in Stochastic Convex Optimization","date":"2022-12-27","arxiv_id":"2212.13556","repositories_listed":0,"syntology":null},{"url":null,"slug":"generalization-bounds-for-transfer-learning","title":"Generalization Bounds for Few-Shot Transfer Learning with Pretrained Classifiers","date":"2022-12-23","arxiv_id":"2212.12532","repositories_listed":0,"syntology":null},{"url":null,"slug":"pac-bayesian-treatment-allocation-under","title":"PAC-Bayesian Treatment Allocation Under Budget Constraints","date":"2022-12-18","arxiv_id":"2212.09007","repositories_listed":0,"syntology":null},{"url":null,"slug":"generalization-bounds-for-inductive-matrix","title":"Generalization Bounds for Inductive Matrix Completion in Low-noise Settings","date":"2022-12-16","arxiv_id":"2212.08339","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-generalization-and-regularization-via","title":"On Generalization and Regularization via Wasserstein Distributionally Robust Optimization","date":"2022-12-12","arxiv_id":"2212.05716","repositories_listed":0,"syntology":null},{"url":null,"slug":"hedging-against-complexity-distributionally","title":"Hedging Complexity in Generalization via a Parametric Distributionally Robust Optimization Framework","date":"2022-12-03","arxiv_id":"2212.01518","repositories_listed":0,"syntology":null},{"url":null,"slug":"two-facets-of-sde-under-an-information","title":"Two Facets of SDE Under an Information-Theoretic Lens: Generalization of SGD via Training Trajectories and via Terminal States","date":"2022-11-19","arxiv_id":"2211.10691","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-generalized-doubly-robust-learning","title":"A Generalized Doubly Robust Learning Framework for Debiasing Post-Click Conversion Rate Prediction","date":"2022-11-12","arxiv_id":"2211.06684","repositories_listed":0,"syntology":null},{"url":null,"slug":"instance-dependent-generalization-bounds-via","title":"Instance-Dependent Generalization Bounds via Optimal Transport","date":"2022-11-02","arxiv_id":"2211.01258","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-pac-bayesian-generalization-bound-for","title":"A PAC-Bayesian Generalization Bound for Equivariant Networks","date":"2022-10-24","arxiv_id":"2210.13150","repositories_listed":0,"syntology":null},{"url":null,"slug":"pac-bayesian-offline-contextual-bandits-with","title":"PAC-Bayesian Offline Contextual Bandits With Guarantees","date":"2022-10-24","arxiv_id":"2210.13132","repositories_listed":0,"syntology":null},{"url":null,"slug":"theoretical-guarantees-for-domain-adaptation","title":"Theoretical Guarantees for Domain Adaptation with Hierarchical Optimal Transport","date":"2022-10-24","arxiv_id":"2210.13331","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-new-family-of-generalization-bounds-using","title":"A New Family of Generalization Bounds Using Samplewise Evaluated CMI","date":"2022-10-12","arxiv_id":"2210.06422","repositories_listed":0,"syntology":null},{"url":null,"slug":"evaluated-cmi-bounds-for-meta-learning","title":"Evaluated CMI Bounds for Meta Learning: Tightness and Expressiveness","date":"2022-10-12","arxiv_id":"2210.06511","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-importance-of-gradient-norm-in-pac","title":"On the Importance of Gradient Norm in PAC-Bayesian Bounds","date":"2022-10-12","arxiv_id":"2210.06143","repositories_listed":0,"syntology":null},{"url":null,"slug":"task-free-continual-learning-via-online","title":"Task-Free Continual Learning via Online Discrepancy Distance Learning","date":"2022-10-12","arxiv_id":"2210.06579","repositories_listed":0,"syntology":null},{"url":null,"slug":"contrastive-learning-can-find-an-optimal","title":"Contrastive Learning Can Find An Optimal Basis For Approximately View-Invariant Functions","date":"2022-10-04","arxiv_id":"2210.01883","repositories_listed":0,"syntology":null},{"url":null,"slug":"scale-invariant-bayesian-neural-networks-with","title":"Scale-invariant Bayesian Neural Networks with Connectivity Tangent Kernel","date":"2022-09-30","arxiv_id":"2209.15208","repositories_listed":0,"syntology":null},{"url":null,"slug":"approximate-description-length-covering","title":"Approximate Description Length, Covering Numbers, and VC Dimension","date":"2022-09-26","arxiv_id":"2209.12882","repositories_listed":0,"syntology":null},{"url":null,"slug":"generalization-bounds-for-stochastic-gradient","title":"Generalization Bounds for Stochastic Gradient Descent via Localized $\\varepsilon$-Covers","date":"2022-09-19","arxiv_id":"2209.08951","repositories_listed":0,"syntology":null},{"url":null,"slug":"extrapolation-and-spectral-bias-of-neural","title":"Extrapolation and Spectral Bias of Neural Nets with Hadamard Product: a Polynomial Net Study","date":"2022-09-16","arxiv_id":"2209.07736","repositories_listed":0,"syntology":null},{"url":null,"slug":"stability-and-generalization-for-markov-chain","title":"Stability and Generalization for Markov Chain Stochastic Gradient Methods","date":"2022-09-16","arxiv_id":"2209.08005","repositories_listed":0,"syntology":null},{"url":null,"slug":"decentralized-learning-with-separable-data","title":"On Generalization of Decentralized Learning with Separable Data","date":"2022-09-15","arxiv_id":"2209.07116","repositories_listed":0,"syntology":null},{"url":null,"slug":"generalization-bounds-for-deep-transfer","title":"Generalization Bounds for Deep Transfer Learning Using Majority Predictor Accuracy","date":"2022-09-13","arxiv_id":"2209.05709","repositories_listed":0,"syntology":null},{"url":null,"slug":"graph-polynomial-convolution-models-for-node","title":"Graph Polynomial Convolution Models for Node Classification of Non-Homophilous Graphs","date":"2022-09-12","arxiv_id":"2209.05020","repositories_listed":0,"syntology":null},{"url":null,"slug":"generalization-in-multi-objective-machine","title":"Generalization In Multi-Objective Machine Learning","date":"2022-08-29","arxiv_id":"2208.13499","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-novel-plug-and-play-approach-for","title":"A Novel Plug-and-Play Approach for Adversarially Robust Generalization","date":"2022-08-19","arxiv_id":"2208.09449","repositories_listed":0,"syntology":null},{"url":null,"slug":"teacher-guided-training-an-efficient","title":"Teacher Guided Training: An Efficient Framework for Knowledge Transfer","date":"2022-08-14","arxiv_id":"2208.06825","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-rademacher-complexity-based-generalization","title":"On Rademacher Complexity-based Generalization Bounds for Deep Learning","date":"2022-08-08","arxiv_id":"2208.04284","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-leave-one-out-conditional-mutual","title":"On Leave-One-Out Conditional Mutual Information For Generalization","date":"2022-07-01","arxiv_id":"2207.00581","repositories_listed":0,"syntology":null},{"url":null,"slug":"robustness-implies-generalization-via-data","title":"Robustness Implies Generalization via Data-Dependent Generalization Bounds","date":"2022-06-27","arxiv_id":"2206.13497","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-how-to-avoid-exacerbating-spurious","title":"On how to avoid exacerbating spurious correlations when models are overparameterized","date":"2022-06-25","arxiv_id":"2206.12739","repositories_listed":0,"syntology":null},{"url":null,"slug":"cold-posteriors-through-pac-bayes","title":"Cold Posteriors through PAC-Bayes","date":"2022-06-22","arxiv_id":"2206.11173","repositories_listed":0,"syntology":null},{"url":null,"slug":"data-augmentation-vs-equivariant-networks-a","title":"Data Augmentation vs. Equivariant Networks: A Theory of Generalization on Dynamics Forecasting","date":"2022-06-19","arxiv_id":"2206.09450","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-role-of-generalization-in","title":"On the Role of Generalization in Transferability of Adversarial Examples","date":"2022-06-18","arxiv_id":"2206.09238","repositories_listed":0,"syntology":null},{"url":null,"slug":"provable-generalization-of-overparameterized","title":"Provable Generalization of Overparameterized Meta-learning Trained with SGD","date":"2022-06-18","arxiv_id":"2206.09136","repositories_listed":0,"syntology":null},{"url":null,"slug":"generalization-bounds-for-data-driven","title":"Generalization Bounds for Data-Driven Numerical Linear Algebra","date":"2022-06-16","arxiv_id":"2206.07886","repositories_listed":0,"syntology":null},{"url":null,"slug":"max-margin-works-while-large-margin-fails","title":"Max-Margin Works while Large Margin Fails: Generalization without Uniform Convergence","date":"2022-06-16","arxiv_id":"2206.07892","repositories_listed":0,"syntology":null},{"url":null,"slug":"memory-classifiers-two-stage-classification","title":"Memory Classifiers: Two-stage Classification for Robustness in Machine Learning","date":"2022-06-10","arxiv_id":"2206.05323","repositories_listed":0,"syntology":null},{"url":null,"slug":"what-is-a-good-metric-to-study-generalization","title":"What is a Good Metric to Study Generalization of Minimax Learners?","date":"2022-06-09","arxiv_id":"2206.04502","repositories_listed":0,"syntology":null},{"url":null,"slug":"boosting-the-confidence-of-generalization-for","title":"Boosting the Confidence of Generalization for $L_2$-Stable Randomized Learning Algorithms","date":"2022-06-08","arxiv_id":"2206.03834","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-bridging-algorithm-and-theory-for","title":"Reconsidering Learning Objectives in Unbiased Recommendation with Unobserved Confounders","date":"2022-06-07","arxiv_id":"2206.03851","repositories_listed":0,"syntology":null},{"url":null,"slug":"dimension-independent-generalization-of-dp","title":"Dimension Independent Generalization of DP-SGD for Overparameterized Smooth Convex Optimization","date":"2022-06-03","arxiv_id":"2206.01836","repositories_listed":0,"syntology":null},{"url":null,"slug":"optimal-weak-to-strong-learning","title":"Optimal Weak to Strong Learning","date":"2022-06-03","arxiv_id":"2206.01563","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-communication-efficient-algorithm-with","title":"A Communication-efficient Algorithm with Linear Convergence for Federated Minimax Learning","date":"2022-06-02","arxiv_id":"2206.01132","repositories_listed":0,"syntology":null},{"url":null,"slug":"vc-theoretical-explanation-of-double-descent","title":"VC Theoretical Explanation of Double Descent","date":"2022-05-31","arxiv_id":"2205.15549","repositories_listed":0,"syntology":null},{"url":null,"slug":"generalization-bounds-and-algorithms-for-1","title":"Generalization bounds and algorithms for estimating conditional average treatment effect of dosage","date":"2022-05-29","arxiv_id":"2205.14692","repositories_listed":0,"syntology":null},{"url":null,"slug":"uniform-convergence-and-generalization-for","title":"Generalization Bounds of Nonconvex-(Strongly)-Concave Stochastic Minimax Optimization","date":"2022-05-28","arxiv_id":"2205.14278","repositories_listed":0,"syntology":null},{"url":null,"slug":"generalization-bounds-for-gradient-methods","title":"Generalization Bounds for Gradient Methods via Discrete and Continuous Prior","date":"2022-05-27","arxiv_id":"2205.13799","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-distributions-by-generative","title":"Learning Distributions by Generative Adversarial Networks: Approximation and Generalization","date":"2022-05-25","arxiv_id":"2205.12601","repositories_listed":0,"syntology":null},{"url":null,"slug":"uniform-generalization-bound-on-time-and","title":"Uniform Generalization Bound on Time and Inverse Temperature for Gradient Descent Algorithm and its Application to Analysis of Simulated Annealing","date":"2022-05-25","arxiv_id":"2205.12959","repositories_listed":0,"syntology":null},{"url":"/paper/sepit-approaching-a-single-channel-speech","slug":"sepit-approaching-a-single-channel-speech","title":"SepIt: Approaching a Single Channel Speech Separation Bound","date":"2022-05-24","arxiv_id":"2205.11801","repositories_listed":0,"syntology":null},{"url":null,"slug":"generalization-bounds-on-multi-kernel","title":"Generalization Bounds on Multi-Kernel Learning with Mixed Datasets","date":"2022-05-15","arxiv_id":"2205.07313","repositories_listed":0,"syntology":null},{"url":null,"slug":"formal-limitations-of-sample-wise-information","title":"Formal limitations of sample-wise information-theoretic generalization bounds","date":"2022-05-13","arxiv_id":"2205.06915","repositories_listed":0,"syntology":null},{"url":null,"slug":"stabilized-doubly-robust-learning-for","title":"StableDR: Stabilized Doubly Robust Learning for Recommendation on Data Missing Not at Random","date":"2022-05-10","arxiv_id":"2205.04701","repositories_listed":0,"syntology":null},{"url":null,"slug":"theory-of-quantum-generative-learning-models","title":"Power of Quantum Generative Learning","date":"2022-05-10","arxiv_id":"2205.04730","repositories_listed":0,"syntology":null},{"url":null,"slug":"dynamical-simulation-via-quantum-machine","title":"Dynamical simulation via quantum machine learning with provable generalization","date":"2022-04-21","arxiv_id":"2204.10269","repositories_listed":0,"syntology":null},{"url":null,"slug":"out-of-distribution-generalization-for","title":"Out-of-distribution generalization for learning quantum dynamics","date":"2022-04-21","arxiv_id":"2204.10268","repositories_listed":0,"syntology":null},{"url":null,"slug":"higher-order-generalization-bounds-learning","title":"Higher-Order Generalization Bounds: Learning Deep Probabilistic Programs via PAC-Bayes Objectives","date":"2022-03-30","arxiv_id":"2203.15972","repositories_listed":0,"syntology":null},{"url":null,"slug":"generalization-bounds-for-learning-under","title":"Generalization bounds for learning under graph-dependence: A survey","date":"2022-03-25","arxiv_id":"2203.13534","repositories_listed":0,"syntology":null},{"url":null,"slug":"rate-distortion-theoretic-generalization","title":"Rate-Distortion Theoretic Generalization Bounds for Stochastic Learning Algorithms","date":"2022-03-04","arxiv_id":"2203.02474","repositories_listed":0,"syntology":null},{"url":null,"slug":"stability-vs-implicit-bias-of-gradient","title":"Stability vs Implicit Bias of Gradient Methods on Separable Data and Beyond","date":"2022-02-27","arxiv_id":"2202.13441","repositories_listed":0,"syntology":null},{"url":null,"slug":"sample-efficiency-of-data-augmentation","title":"Sample Efficiency of Data Augmentation Consistency Regularization","date":"2022-02-24","arxiv_id":"2202.12230","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-unsupervised-domain-adaptation-via","title":"Towards Unsupervised Domain Adaptation via Domain-Transformer","date":"2022-02-24","arxiv_id":"2202.13777","repositories_listed":0,"syntology":null},{"url":null,"slug":"connecting-optimization-and-generalization","title":"From Optimization Dynamics to Generalization Bounds via Łojasiewicz Gradient Inequality","date":"2022-02-22","arxiv_id":"2202.10670","repositories_listed":0,"syntology":null},{"url":null,"slug":"convex-loss-functions-for-contextual-pricing","title":"Convex Surrogate Loss Functions for Contextual Pricing with Transaction Data","date":"2022-02-16","arxiv_id":"2202.10944","repositories_listed":0,"syntology":null},{"url":null,"slug":"black-box-generalization","title":"Black-Box Generalization: Stability of Zeroth-Order Learning","date":"2022-02-14","arxiv_id":"2202.06880","repositories_listed":0,"syntology":null},{"url":null,"slug":"relaxing-the-feature-covariance-assumption","title":"Towards Data-Algorithm Dependent Generalization: a Case Study on Overparameterized Linear Regression","date":"2022-02-12","arxiv_id":"2202.06054","repositories_listed":0,"syntology":null},{"url":null,"slug":"generalization-bounds-via-convex-analysis","title":"Generalization Bounds via Convex Analysis","date":"2022-02-10","arxiv_id":"2202.04985","repositories_listed":0,"syntology":null},{"url":null,"slug":"improved-information-theoretic-generalization","title":"Improved Information Theoretic Generalization Bounds for Distributed and Federated Learning","date":"2022-02-04","arxiv_id":"2202.02423","repositories_listed":0,"syntology":null},{"url":null,"slug":"generalization-in-cooperative-multi-agent","title":"Generalization in Cooperative Multi-Agent Systems","date":"2022-01-31","arxiv_id":"2202.00104","repositories_listed":0,"syntology":null},{"url":null,"slug":"with-greater-distance-comes-worse-performance","title":"With Greater Distance Comes Worse Performance: On the Perspective of Layer Utilization and Model Generalization","date":"2022-01-28","arxiv_id":"2201.11939","repositories_listed":0,"syntology":null},{"url":null,"slug":"generalization-in-supervised-learning-through","title":"Generalization in Supervised Learning Through Riemannian Contraction","date":"2022-01-17","arxiv_id":"2201.06656","repositories_listed":0,"syntology":null},{"url":null,"slug":"stability-based-generalization-bounds-for-1","title":"Stability Based Generalization Bounds for Exponential Family Langevin Dynamics","date":"2022-01-09","arxiv_id":"2201.03064","repositories_listed":0,"syntology":null},{"url":null,"slug":"barack-partially-supervised-group-robustness","title":"BARACK: Partially Supervised Group Robustness With Guarantees","date":"2021-12-31","arxiv_id":"2201.00072","repositories_listed":0,"syntology":null}],"record_sha256":"329f2c419282e8e7c84755c835bb22357463d942d9d7ee6cca8fc126f4c6b328","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}