Stochastic Approximation

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14 papers in the last four weeks, up 250% on the four weeks before. 0.1% of all new papers.

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  1. Best of Both Worlds in Federated LSA: Speedup When Possible, Personalization Always

    Oct 8, 2026Safwan Labbi, Paul Mangold, Eric MoulinesFederated LearningHeterogeneous Federated Learning

    CMAP, CNRS, École Polytechnique, Institut Polytechnique de Paris, 91120 Palaiseau, France · Mohamed bin Zayed University of Artificial Intelligence, UAE · LRE EPITA, 94270 Le Kremlin-Bicêtre, France

  2. Stationary Bias and Extrapolation in Nonlinear Two-Timescale Stochastic Approximation

    Oct 7, 2026A. Ch. Madhusudanarao, Rahul SinghStochastic ApproximationTwo-Timescale Stochastic Approximation

    Department of Computer Science and Automation Indian Institute of Science, Bengaluru, India · Laboratoire de Recherche de l’EPITA, Paris, France

  3. What a Reporting Convention Hides: A Matched-Budget Audit of Quantum Natural Gradient with an Exactly Computed Metric

    Oct 7, 2026Lu Wei, Yufeng Wang, Haibin LingQuantum Machine LearningVariational Quantum Algorithms

    Stony Brook University · Westlake University

  4. Moment-Accurate Gaussian Mixtures for Constant-Step Stochastic Approximation

    Oct 4, 2026Xiaoli Li, Wei Biao WuGaussian Mixture ModelsStochastic Approximation

    University of Chicago

  5. Sharp Stationary Gaussian Approximation for Constant-Stepsize SGD

    Sep 30, 2026Junghoon SeoStochastic ApproximationStochastic Gradient Descent

    PIT IN Corp., South Korea

  6. Sharp Statistical Rates for Asynchronous TD Learning with Markovian Data

    Sep 30, 2026Yang PengAsynchronous RLStochastic Approximation

    Yau Mathematical Sciences Center, Tsinghua University

  7. Second-Moment Stochastic Approximation Methods

    Sep 29, 2026Tao Jiang, Lin XiaoStochastic ApproximationMuon Optimizer

    Fundamental AI Research (FAIR), Meta Superintelligence Labs

  8. Finite-Time Concentration and Convergence Rates for Projected Two-Time-Scale Stochastic Approximation with Markov Noise

    Sep 28, 2026Rahul Singh, Vivek S. Borkar, Eric MoulinesLast-Iterate ConvergenceStochastic Approximation

    Laboratoire de Recherche de l’EPITA, Paris, France · Indian Institute of Technology Bombay · Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates

  9. A Contraction Framework for Stochastic Operators with Bootstrapping: Application to TD Learning

    Sep 24, 2026Ids van der Werf, Sergio Rozada, Antonio G. MarquesStochastic ApproximationTemporal-Difference Learning

    Delft University of Technology, Dep. Microelectronics, Delft, The Netherlands

  10. Distributed Stochastic Approximation Algorithms and Heavy-Tailed Age of Information

    Sep 23, 2026Adrian Redder, Arunselvan Ramaswamy, Holger KarlStochastic ApproximationAge of Information

    Dept. of Electrical Engineering and Information Technology, Paderborn University, Germany · Dept. of Industrial Engineering and Operations Research, Indian Institute of Technology Bombay, India · Hasso-Plattner Institute (HPI), Digital Engineering Faculty, University of Potsdam, Germany

  11. Polyak-Type Extragradient Methods for Monotone Root-Finding Problems

    Sep 22, 2026TaeHo Yoon, Sayantan Choudhury, Ezra Greenberg +1Stochastic Approximation

    Department of Applied Mathematics & Statistics Mathematical Institute for Data Science (MINDS) Johns Hopkins University

  12. Locally Private Inference for Riemannian Stochastic Optimization

    Sep 18, 2026Xiaotian Chang, Yangdi Jiang, Qirui HuRiemannian OptimizationConfidence Region Estimation

    School of Physical and Mathematical Sciences, Nanyang Technological University · School of Statistics and Data Science, Shanghai University of Finance and Economics.

  13. The Bias of Nonlinear Two-Time-scale Stochastic Approximation under Constant Step-Sizes

    Sep 17, 2026Djamel Rassem Lamouri, Dorian Baudry, Nicolas GastStochastic ApproximationTwo-Timescale Stochastic Approximation

    Univ. Grenoble Alpes, CNRS, Inria Grenoble INP, LIG, 38000 Grenoble France

  14. Improving the Last-Iterate Guarantees of Anytime Algorithms for Stochastic Monotone Variational Inequalities

    Sep 14, 2026Jun-Hyun Kim, Ahmet AlacaogluLast-Iterate ConvergenceStochastic Approximation

    University of British Columbia, Vancouver. · Department of Mathematics, University of British Columbia, Vancouver.

  15. Inference for Newton Methods with Accelerated Sketch-and-Project via Random Scaling

    Sep 14, 2026Xinchen Du, Elizaveta Rebrova, Micha\l Dereziński +1Stochastic ApproximationSecond-Order Optimization

    School of Industrial and Systems Engineering, Georgia Institute of Technology · Department of Operations Research and Financial Engineering, Princeton University · Computer Science and Engineering, University of Michigan

  16. Steady-State Convergence of Stochastic Approximation

    Sep 14, 2026Yixuan Zhang, Qiaomin XieStochastic ApproximationQ-Learning

    Department of Industrial & Systems Engineering, University of Wisconsin–Madison

  17. Oracle Complexity of Stochastic Fixed-Point Equations with Nonexpansive Maps

    Sep 8, 2026Jelena Diakonikolas, Cristóbal Guzmán, David Martínez-RubioOracle ComplexityStochastic Approximation

    Department of Computer Sciences, University of Wisconsin-Madison · Institute for Mathematical and Computational Engineering, Faculty of Mathematics and School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile · IMDEA Software Institute, Madrid, Spain

  18. Convergence rates for the RMSprop optimizer with full control of the hyperparameters

    Aug 31, 2026Steffen Dereich, Arnulf JentzenStochastic ApproximationStochastic Optimization Convergence

  19. A Finite-Sample Analysis of Quantile Temporal-Difference Learning

    Aug 27, 2026Zijie Cheng, Xiang Li, Yang Peng +1Distributional RLStochastic Approximation

    School of Mathematical Sciences, Peking University · Perelman School of Medicine, University of Pennsylvania · Yau Mathematical Sciences Center, Tsinghua University

  20. Direct Acceleration of Stochastic Root-Finding Without Variance Reduction and Regularization

    Aug 12, 2026TaeHo Yoon, Nicolas LoizouStochastic Approximation

    Department of Applied Mathematics and Statistics & Mathematical Institute for Data Science, Johns Hopkins University

  21. Self-Normalized Inference for Constant-Stepsize Temporal-Difference Learning under Markovian Sampling

    Aug 11, 2026Min Zeng, Yichen Zhang, Xiaofeng ShaoConfidence Region EstimationStochastic Approximation

    Department of Biostatistics, City University of Hong Kong, Hong Kong SAR, China · Department of Quantitative Methods, Purdue University, West Lafayette, Indiana, USA · Department of Statistics and Data Science, Washington University in St. Louis, St. Louis, Missouri, USA +1

  22. Stochastic gradient descent with discontinuity across a manifold

    Aug 7, 2026Vivek S. BorkarStochastic ApproximationGradient Descent Dynamics

    Department of Electrical Engineering, Indian Institute of Technology Bombay, Powai, Mumbai 400076, INDIA.

  23. Concentration and Mean-Square Bounds for Contractive Stochastic Approximation: A Unified Elementary Approach

    Jul 20, 2026Siddharth ChandakStochastic Approximation

    Department of Electrical Engineering, Stanford University, Stanford, 94305, CA, USA

  24. Non-Expansive Two-Time-Scale Stochastic Approximation: A Fixed-Schedule One-Quarter Barrier and Bias-Corrected Acceleration

    Jul 15, 2026Dhruv Sarkar, Vaneet AggarwalLast-Iterate ConvergenceStochastic Approximation

    Indian Institute of Technology Kharagpur · Mohamed bin Zayed University of Artificial Intelligence · Purdue University

  25. Solving Stochastic Fixed-Point Equations with High Probability

    Jul 10, 2026Jelena DiakonikolasStochastic ApproximationStochastic Optimization Convergence

    Department of Computer Sciences University of Wisconsin-Madison

  26. Adaptive MPPI with Online Disturbance Covariance Estimation: Provable Stability Tightening via Spatial Smoothing

    Jul 9, 2026Hyung-Jin Yoon, Hunmin KimLyapunov StabilityStochastic Approximation

    Department of Mechanical and Nuclear Engineering, Tennessee Technological University, Cookeville, TN, USA

  27. A Single Stepsize Suffices for Unprojected Linear TD(0): Simultaneous Robust and Fast Rates via Polyak--Ruppert Averaging

    Jun 23, 2026Wei-Cheng Lee, Francesco OrabonaStochastic ApproximationTemporal-Difference Learning

    King Abdullah University of Science and Technology (KAUST) Thuwal, 23955-6900, Kingdom of Saudi Arabia

  28. Distribution-Aware Robust Bilevel Optimization: Quantile-Guided Huber Updates in Two-Timescale Stochastic Approximation

    Jun 21, 2026Zhiyu Li, Xi Xuan, Davide CarboneStochastic OptimizationStochastic Approximation

    University of Science and Technology of China Hefei, China · City University of Hong Kong Hong Kong SAR, China · Laboratoire de Physique de l’École Normale Supérieure, Université PSL, CNRS, Sorbonne Université, Université de Paris Paris, France

  29. Escaping the Variance Trap: Jacobian-Free Dynamics for Root-Finding Bilevel Optimization

    Jun 21, 2026Zhiyu Li, Xi Xuan, Davide CarboneStochastic ApproximationBilevel Optimization

    University of Science and Technology of China · City University of Hong Kong · Laboratoire de Physique de l’École Normale Supérieure, Université PSL, CNRS, Sorbonne Université, Université de Paris

  30. Central limit theorem for the averaged Adam optimizer

    Jun 19, 2026Steffen Dereich, Arnulf JentzenStochastic ApproximationStochastic Optimization Convergence

    Institute for Mathematical Stochastics, University of Münster, Germany · School of Data Science and School of Artificial Intelligence, The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen), China · Applied Mathematics: Institute for Analysis and Numerics, University of Münster, Germany