Optimal Sample Complexity

Ask about this field

Recent momentum

emerging

0 papers in the last 28 days · 0.0% of indexed attention

Twelve weeks of publication activity for this topic as it is defined today.

Weekly history

Recent digests

What was published in this field, kept on the site without email delivery.

Period ending 2026-09-21

13 new papers

A weekly snapshot of new work published in Optimal Sample Complexity.

Period ending 2026-09-14

13 new papers

A weekly snapshot of new work published in Optimal Sample Complexity.

Period ending 2026-09-07

6 new papers

A weekly snapshot of new work published in Optimal Sample Complexity.

Inside this field

Focused directions

424 papers

Latest in Optimal Sample Complexity

Browse all topics →
CardsList

  1. Optimal Top-kk Identification from Pairwise Comparisons

    Jul 9, 2026Motti Goldberger, Nils RudiOptimal Sample ComplexityTop-K

  2. High-Dimensional Procrustes Matching via Tree Counts

    Jul 9, 2026Xiaochun Niu, Tselil Schramm, Jiaming XuHigh-Dimensional DataFeature Matching

  3. Tubular Neighbourhoods of Pfaffian Sets and Applications to Neural Networks

    Jul 9, 2026Paul Lezeau, Martin LotzNeural NetworkNew Bounds

  4. Learning AC0\mathsf{AC}^0 under Locally Sampleable Graphical Models

    Jul 9, 2026Weiming Feng, Xiongxin Yang, Yixiao Yu +1Optimal Sample ComplexitySingular Learning Theory

  5. Near-Optimal Learning of Gaussian Sobolev Operators

    Jul 8, 2026Ben Adcock, Michael Griebel, Gregor MaierLogarithmic Sobolev InequalitiesProbabilistic Operator Learning

  6. Distributed Sketching on Data Partitions for OLS Regression

    Jul 8, 2026Luyuan Yang, Brayden Garner, Shayan Shafaei +1Least SquaresPartitioning

  7. The Optimal Sample Complexity of Learning Autoregressive Chain-of-Thought

    Jul 8, 2026Zhiyuan LiOptimal Sample ComplexitySample Complexity

  8. Is Randomness Necessary for Adaptive Data Analysis?

    Jul 8, 2026Edith Cohen, Haim Kaplan, Yishay Mansour +2Optimal Sample ComplexityData Collection

  9. On Explicit Super-Expressive Approximation for Neural Networks

    Jul 7, 2026Feng-Lei Fan, Ze-Yu Li, Chen-Yu Wang +1Neural-Network ApproximationApproximation

  10. When Does In-Context Search Help? A Sampling-Complexity Theory of Reflection-Driven Reasoning

    Jul 7, 2026Yotam Wolf, Noam Wies, Amnon ShashuaLarge Language Model ReasoningIn-Context

  11. Fast determinantal sampling on general spaces and diffusion geometry

    Jul 7, 2026Hoang-Son Tran, Pranav Gupta, Subhroshekhar GhoshDeterminantal Point ProcessOptimal Sample Complexity

  12. Data-dependent Evaluations for Budgeted Submodular Maximization

    Jul 7, 2026Lejian Zhang, Xueyan Tang, Jing TangSubmodular MaximizationKnapsack Constraint

  13. Deep Neural Variation Spaces: A Unifying Perspective on Depth and Complexity

    Jul 6, 2026Julia Nakhleh, Robert D. NowakRectified Linear Unit NetworksDeep Network

  14. Active Learning on Adversarially Corrupted Graphs

    Jul 6, 2026Marco Bressan, Nicolò Cesa-Bianchi, Tommaso d`Orsi +2Graph TheoryActive Learning

  15. Selectivity Estimation for Linear Queries via Online Learning

    Jul 3, 2026Fangzhu Shen, Debmalya Panigrahi, Sudeepa RoyLearning-Augmented AlgorithmsSelectivity

  16. Optimal Stabilizer Testing and Learning with Limited Quantum Memory

    Jul 2, 2026Srinivasan Arunachalam, Louis SchatzkiN$-Qubit Stabilizer StatesSample Complexity

  17. Tight Lower Bounds for the Multi-Secretary Problem via Bellman Certificates

    Jul 2, 2026Jiawei ZhangLinear RegretLower Bounds

  18. From Spectral Methods to Sample Complexity Bounds for Fourier Neural Operators

    Jul 1, 2026Nisha Chandramoorthy, Daniel Sanz-Alonso, Nathan WaniorekFourier Neural OperatorsNeural Operators

  19. Distributionally Robust Linear Regression With Block Lewis Weights

    Jun 30, 2026Naren Sarayu Manoj, Kumar Kshitij PatelLeast SquaresProximal Gradient Descent

  20. Sample Complexities of Estimating Gumbel--Max Watermark Proportions with and without Reduction to Pivotal Statistics

    Jun 30, 2026Shuwen Chai, Qiaosen WangWatermarkingWatermarks

  21. Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing

    Jun 30, 2026Eric Shen, Tony Wu, Mahbod Majid +1Conditional IndependenceTemporal Dependence

  22. AI-Assisted Discovery of Convex Relaxations via Dual Agents

    Jun 30, 2026Sungyoon Kim, Mert PilanciUpper BoundsInequalities

  23. Behavior Cloning is Not All You Need: The Optimality of On-Policy Distillation for Noisy Expert Feedback

    Jun 29, 2026Ved Sriraman, Peihan Liu, Daniel Hsu +1On-Policy DistillationImitation Learning

  24. SGD Provably Prioritizes a Shortcut Spurious Feature in the XOR Model

    Jun 29, 2026Tyler LaBonte, Vidya MuthukumarFeature LearningRectified Linear Unit Networks

  25. Adjusted Wasserstein distances for bridging empirical and true distributions with applications to MDS

    Jun 29, 2026Flor Martinez-Sermeno, Arturo Jaramillo, Johan Van HorebeekWasserstein DistanceOptimal Sample Complexity

  26. How AI settled the complexity of the oldest SGD algorithm

    Jun 28, 2026Michał Dereziński, Xiaoyu DongStochastic Gradient DescentWorst-Case

  27. Sample Complexity of Scientific Discovery: PAC Learnability of Compositional Function Trees

    Jun 28, 2026Şuayp Talha Kocabay, Talha Rüzgar Akkuş, Kerem YalçınSymbolic RegressionSample Complexity

  28. Replica Symmetry Breaking and Algorithmic Thresholds in Empirical Risk Minimization under Multi-Index Model

    Jun 26, 2026Andrea Montanari, Kangjie ZhouEmpirical Risk MinimizationOptimal Sample Complexity

  29. Surprises in Proper Positive-Only Learning

    Jun 26, 2026Shai Ben-David, Farnam Mansouri, Anay Mehrotra +1Binary ClassificationOptimal Sample Complexity

  30. Graph Dimensionality Reduction for Contextual Bandits: Structure-Specific Regret Bounds under Approximate Smoothness and Noisy Eigenspaces

    Jun 26, 2026Joyanta Jyoti Mondal, Ibne Farabi Shihab, Anuj SharmaLinear Contextual BanditsMulti-Armed Bandits

  31. Fast algorithms for learning a Gaussian under halfspace truncation with optimal sample complexity

    Jun 25, 2026Haitong Liu, Deepak Narayanan Sridharan, David Steurer +1Optimal Sample ComplexityGaussian Mixture Models

  32. Asymptotically Optimal Learning for Parametric Prophet Inequalities

    Jun 25, 2026Jung-hun Kim, Anna Grebennikova, Vianney PerchetConcentration InequalitiesOptimal Policies

  33. Sketched Linear Contrastive Learning: Approximation, Optimization, and Statistical Scaling

    Jun 25, 2026Ziyan Chen, Zhongzhu Zhou, Ding-Xuan ZhouContrastive LearningScaling Laws

  34. High-Probability PL-SGD with Markovian Noise: Optimal Mixing and Tail Dependence

    Jun 24, 2026Dhruv Sarkar, Aprameyo Chakrabartty, Vaneet AggarwalStochastic Gradient DescentLong-Tailed Distribution

  35. Variable Bound Tightening for Nash Equilibrium Computation in Multiplayer Imperfect-Information Games

    Jun 24, 2026Sam GanzfriedNash EquilibriumImperfect-Information Games

  36. Space-Efficient Language Generation in the Limit

    Jun 24, 2026Nicolas Flammarion, Chirag Pabbaraju, Hristo Papazov +2Context-Free GrammarsData Generation

  37. New Bounds for the Last Iterate of the Stochastic subGradient Method

    Jun 23, 2026Guglielmo Beretta, Tommaso Cesari, Roberto Colomboni +1Stochastic Smooth Convex OptimizationLarge Step Sizes

  38. Sample complexity of unbalanced entropic OT

    Jun 23, 2026Francisco Andrade, Gabriel Peyré, Clarice PoonEntropy-Regularized Equilibrium SelectionOptimal Sample Complexity

  39. Uniform Sampling from High-dimensional Spectral Norm Balls

    Jun 23, 2026Michael R. MetelSpectral NormSingular Value Decomposition

  40. Exact Schur-Sylvester Dimensionality Reductions for Non-Smooth Stochastic Complexity and Manifold Sampling

    Jun 22, 2026Trenton Lau, Gary P. T. ChoiMaximum LikelihoodOptimal Sample Complexity

  41. Are Safety Guarantees in Neural Networks Safe? How to Compute Trustworthy Robustness Certifications

    Jun 22, 2026Merkouris Papamichail, Konstantinos Varsos, Giorgos Flouris +1Neural Network VerificationCertification

  42. Diffusion Models Adapt to Low-Dimensional Structure Under Flexible Coefficient Choices

    Jun 22, 2026Changxiao Cai, Yuchen Jiao, Gen LiDiffusion SamplingLow-Dimensional Structure

  43. Non-asymptotic estimates of the minimal risk in statistical learning

    Jun 22, 2026Liming Wu, Sen YangEmpirical Risk MinimizationConcentration Inequalities

  44. Minimax Quantile Lower Bounds for Interactive Statistical Decision Making with Privacy

    Jun 22, 2026Raghav Bongole, Amirreza Zamani, Tobias J. Oechtering +1MinimaxGeneralized Linear Bandit

  45. Geometry-Aware Online Scheduling for LLM Serving: From Theoretical Bound to System Practice

    Jun 21, 2026Li Kong, Qi Qi, Yinyu Ye +1Large Language Model ServingOptimal Scheduling

  46. Quantifying Theoretical AI Alignment Guarantees: Receiver-Utility Bounds in Bayesian Persuasion

    Jun 20, 2026Eric Yachbes, Eva TardosArtificial Intelligence AlignmentPersuasion

  47. Rebuttals Move Peer-Review Scores, but Initial-Review Structure Bounds the Movement

    Jun 20, 2026Mathieu Louis, Tibo Vanleke, Vincent Ginis +1Peer ReviewReviewer

  48. On the Curse of Dimensionality in Private Sparse Covariance Estimation and PCA

    Jun 20, 2026Syamantak Kumar, Shourya Pandey, Purnamrita Sarkar +1Differential PrivacyPrincipal Component Analysis

  49. Breaking chains with trees: Deep learning with O(log⁡N)\mathcal{O}(\log N) parallel time complexity

    Jun 19, 2026Neeraj Mohan Sushma, Aditya Nagarsekar, Cabrel Teguemne Fokam +4BackpropagationNeural Architectures

  50. Gradient-Free Warm-Start Library Recovery: an Amortized-Regret Separation

    Jun 19, 2026Jianwei LouLearning-Augmented AlgorithmsCold-Start

  51. Optimal Deterministic Multicalibration and Omniprediction

    Jun 18, 2026Georgy Noarov, Aaron RothMulticalibration and CalibrationOptimal Sample Complexity

  52. Beyond Averaging in John Ellipsoid Approximation: High-Accuracy Algorithms in the Leverage-Score Model

    Jun 18, 2026Xiaoyu Li, Junwei Yu, Jiaojiao Jiang +2Optimal Sample ComplexityPolytopes

  53. Kernel of Partition Paths: A Unified Representation for Tree Ensembles

    Jun 17, 2026Nicolas MahlerDecision TreesKernel Method

  54. Exponentially many initializations to avoid barren plateaus

    Jun 16, 2026Ankit Kulshrestha, Ricard Puig, Diego García-Martín +4Worst-CaseConcentration Inequalities

  55. Sign-Rank, Index, and List Replicability: Connections and Separations

    Jun 16, 2026Ari Blondal, Hamed Hatami, Pooya Hatami +2Lower BoundsTwo-Sample Testing

  56. Bounded Difference Concentration for Infinitely Exchangeable Sequences with Applications to AI Benchmark Uncertainty

    Jun 16, 2026Fangyuan Lin, Spencer Frei, Victor H. de la PenaConcentration InequalitiesArtificial Intelligence Benchmarks

  57. Tight L∞L_\infty Sample Complexity for Low-Degree and Sparse Boolean Polynomials

    Jun 15, 2026Jasper van Doornmalen, Mathieu Molina, Victor Verdugo +1Optimal Sample ComplexitySample Complexity

  58. Sobolev Approximation by Fixed-Size Neural Networks with Arbitrary Accuracy

    Jun 15, 2026Baicheng Li, Haizhao Yang, Shijun ZhangNeural-Network ApproximationLogarithmic Sobolev Inequalities

  59. Upper Bounds on the Generalization Error of Deep Learning Models via Local Robustness and Stability

    Jun 15, 2026Abdul-Rauf Nuhu, Parham M. Kebria, Vahid Hemmati +3Generalization BoundsUpper Bounds

  60. Learning Policy from a Single Trajectory in Average-Reward Markov Decision Process

    Jun 15, 2026Jongmin Lee, Ernest K. Ryu, Vaneet AggarwalMarkov Decision ProcessesModel-Free Reinforcement Learning