Statistical Learning Theory

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34 papers in the last four weeks, up 127% on the four weeks before. 0.3% of all new papers.

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  1. Effects of Structural Allocation of Geometric Task Diversity in Linear Meta-Learning Models

    Sep 22, 2025Saptati Datta, Nicolas W. Hengartner, Yulia Pimonova +2Meta-LearningFew-Shot Learning

    Department of Statistics, Texas A&M University, TX, USA · Los Alamos National Laboratory, Los Alamos, USA.

  2. A Kernel-based Stochastic Approximation Framework for Nonlinear Operator Learning

    Sep 14, 2025Jia-Qi Yang, Lei ShiStochastic ApproximationReproducing Kernel Hilbert Spaces

    School of Mathematical Sciences and Shanghai Key Laboratory for Contemporary Applied Mathematics, Fudan University, Shanghai 200433, China.

  3. A statistical physics framework for optimal learning

    Jul 10, 2025Francesca Mignacco, Francesco MoriStatistical Physics of LearningNeural Network Training Dynamics

    1Joseph Henry Laboratories of Physics, Princeton University, Princeton, NJ 08544, USA · 2Graduate Center, City University of New York, New York, NY 10016, USA · Center of Mathematical Sciences and Applications, Harvard University, Cambridge, MA 02138, USA

  4. Adaptively Truncated Signature-based Logistic Regression for Semi-parametric Functional Classification

    Jul 9, 2025Pengcheng Zeng, Siyuan JiangStatistical Learning Theory

    Institute of Mathematical Sciences, ShanghaiTech University, Shanghai, China

  5. On the Existence of Consistent Adversarial Attacks in High-Dimensional Linear Classification

    Jun 14, 2025Matteo Vilucchio, Lenka Zdeborová, Bruno LoureiroAdversarial AttacksAdversarial Robustness

    Information Learning and Physics Laboratory, École Polytechnique Fédérale de Lausanne (EPFL) · Statistical Physics of Computation Laboratory, École Polytechnique Fédérale de Lausanne (EPFL) · Département d’Informatique, École Normale Supérieure - PSL & CNRS, France

  6. No Free Lunch: Non-Asymptotic Analysis of Prediction-Powered Inference

    May 26, 2025Pranav Mani, Peng Xu, Zachary C. Lipton +1Adaptive InferenceStatistical Learning Theory

    Abridge AI, San Francisco, CA, USA · Machine Learning Department, Carnegie Mellon University, Pittsburgh, PA, USA · Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA

  7. Representation Learning for Equivariant Inference with Guarantees

    May 26, 2025Daniel Ordoñez-Apraez, Vladimir Kostić, Alek Fröhlich +3Disentangled Representation LearningRepresentation Learning

    CSML, Italian Institute of Technology, Genova, Italy · Universit`a di Genova, Genova, Italy · University of Novi Sad, Novi Sad, Serbia +2

  8. When majority rules, minority loses: bias amplification of gradient descent

    May 19, 2025François Bachoc, Jérôme Bolte, Ryan Boustany +1Class-Imbalanced LearningGradient Descent

    LPP · University of Lille · Institut Universitaire de France (IUF) +6

  9. The Dynamics of Generalization in Deep Learning

    Apr 23, 2025Rubing Yang, Pratik ChaudhariNeural Network GeneralizationNeural Network Training Dynamics

    Department of Applied Mathematics and Computational Sciences, University of Pennsylvania Philadelphia, PA, 19104, USA · Department of Electrical and Systems Engineering, University of Pennsylvania Philadelphia, PA, 19104, USA

  10. Learning in Structured Stackelberg Games

    Apr 11, 2025Maria-Florina Balcan, Kiriaki Fragkia, Keegan HarrisGame TheoryStackelberg Games

    Carnegie Mellon University, Pittsburgh, USA · University of California, Berkeley, USA

  11. Recursive Learning Without Collapse: A Weighting-Based Stabilization Framework

    Feb 25, 2025Hengzhi He, Shirong Xu, Guang ChengModel CollapseGenerative Modeling

    Department of Statistics and Data Science, University of California, Los Angeles · Wang Yanan Institute for Studies in Economics, Xiamen University

  12. Optimal and Provable Calibration in High-Dimensional Binary Classification: Angular Calibration and Platt Scaling

    Feb 21, 2025Yufan Li, Pragya SurProbability CalibrationBinary Classification

    Department of Statistics Harvard University Cambrdige, MA 02138

  13. Fixed-Gaussian Spectral Algorithms: Minimax Optimal Rates for Misspecified Learning and Transfer

    Jan 18, 2025Haotian Lin, Matthew ReimherrSpectral RegularizationConcept Drift

    Department of Statistics, The Pennsylvania State University.

  14. The Method of Gaps: Exact Expressions for the Generalization Error of Supervised Learning Algorithms

    Nov 18, 2024Samir M. Perlaza, Xinying ZouInformation-Theoretic Generalization BoundsStatistical Learning Theory

    INRIA, Centre Inria d’Universit´e Cˆote d’Azur, 06902 Sophia Antipolis, France

  15. Discrete distributions are learnable from metastable samples

    Oct 17, 2024Abhijith Jayakumar, Andrey Y. Lokhov, Sidhant Misra +1Conditional Distribution EstimationStatistical Learning Theory

    Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA

  16. Adaptive and oblivious statistical adversaries are equivalent

    Oct 17, 2024Guy Blanc, Gregory ValiantStatistical Learning Theory

    Stanford

  17. On Generalisation Error Bounds for Transformers

    Oct 15, 2024Lan V. TruongTransformerStatistical Learning Theory

    Faculty of Computer Science and Engineering, Ho Chi Minh City University of Technology (HCMUT), Vietnam

  18. Which Spaces can be Embedded in LpL_p-type Reproducing Kernel Banach Space? A Characterization via Metric Entropy

    Oct 14, 2024Yiping Lu, Daozhe Lin, Qiang DuReproducing Kernel Hilbert SpacesKernel Methods

    Industrial Engineering & Management Sciences, Northwestern University · Department of Applied Physics & Applied Mathematics, Columbia University

  19. Statistical Properties of Deep Neural Networks with Dependent Data

    Oct 14, 2024Chad BrownNonparametric RegressionNeural Network Approximation Theory

    Department of Economics, University of Colorado Boulder, 80309, USA.

  20. The EM-algorithm and the Method of Moments in Softmax Mixture Models

    Sep 16, 2024Xin Bing, Florentina Bunea, Jonathan Niles-Weed +1Expectation-MaximizationDiscrete Choice Modeling

    Department of Statistical Sciences, University of Toronto · Department of Statistics and Data Science, Cornell University · Courant Institute of Mathematical Sciences and Center for Data Science, New York University +1

  21. Adversarial dynamical systems characterize when data-driven learning succeeds or fails

    Jul 8, 2024Matthew J. Colbrook, Igor Mezić, Alexei StepanenkoKoopman Operator LearningSpectral Methods

    DAMTP, University of Cambridge, Cambridge, CB3 0WA, UK. · University of California, Santa Barbara, CA 93106, USA.

  22. Smoothed Analysis for Learning Concepts with Low Intrinsic Dimension

    Jul 1, 2024Gautam Chandrasekaran, Adam Klivans, Vasilis Kontonis +2Statistical Learning TheoryMulti-Index Models

    a University of Texas at Austin · b University of California, Los Angeles

  23. Generalization error of min-norm interpolators in transfer learning

    Jun 20, 2024Yanke Song, Kenneth Gu, Sohom Bhattacharya +1OOD GeneralizationCross-Domain Transfer Learning

    Department of Statistics, Harvard University · Department of Statistics, Stanford University · Department of Statistics, University of Florida

  24. Estimation of multiple mean vectors in high dimension

    Mar 22, 2024Gilles Blanchard, Jean-Baptiste Fermanian, Hannah MarienwaldKernel Mean EmbeddingsStatistical Learning Theory

    LMO, DATASHAPE · Université Paris Saclay, Institut Mathématique d’Orsay, France. · LMO +2

  25. A Probabilistic Approach for Model Alignment with Human Comparisons

    Mar 16, 2024Junyu Cao, Mohsen BayatiHuman Preference ModelingStatistical Learning Theory

    McCombs School of Business, The University of Texas at Austin · Graduate School of Business, Stanford University

  26. A Differentially Private Weighted Empirical Risk Minimization Procedure and its Application to Outcome Weighted Learning

    Jul 24, 2023Spencer Giddens, Yiwang Zhou, Kevin R. Krull +3Privacy-Preserving MLDifferential Privacy

    University of Notre Dame, Notre Dame, IN 46556, USA · St. Jude Children’s Research Hospital, Memphis, TN 38138, USA · University of Michigan, Ann Arbor, MI 48109, USA

  27. Reliable learning in challenging environments

    Apr 6, 2023Maria-Florina Balcan, Steve Hanneke, Rattana Pukdee +1Distribution Shift RobustnessAdversarial Robustness

    Carnegie Mellon University · Purdue University

  28. Distribution-free Deviation Bounds and The Role of Domain Knowledge in Learning via Model Selection with Cross-validation Risk Estimation

    Mar 15, 2023Diego Marcondes, Cláudia PeixotoModel SelectionStatistical Learning Theory

  29. How many labelers do you have? A closer look at gold-standard labels

    Jun 24, 2022Chen Cheng, Hilal Asi, John DuchiModel CalibrationNoisy-Label Learning

    Department of Statistics, Stanford University · Department of Electrical Engineering, Stanford University · Departments of Statistics and Electrical Engineering, Stanford University

  30. Learning Non-Vacuous Generalization Bounds from Optimization

    Jun 9, 2022Chengli Tan, Jiangshe Zhang, Junmin Liu +1Neural Network GeneralizationStatistical Learning Theory

    Northwestern Polytechnical University, Xi’an, China · Xi’an Jiaotong University, Xi’an, China · SGIT AI Lab, State Grid Corporation of China, Xi’an, China