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2 papers in the last 28 days · 0.1% of indexed attention

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Period ending 2026-09-14

1 new paper

A weekly snapshot of new work published in Optimal Learner.

39 papers

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  1. Bridging Control, Inference, Transport, and Thermodynamics: From Theory to Applications in Learning

    Sep 14, 2026Emmy Blumenthal, Nikolas Claussen, Benjamin Eysenbach +4Optimal LearnerKullback-Leibler Regularization

  2. Steady-State Convergence of Stochastic Approximation

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

  3. PAC-Bayesian Bounds for Learning Partially Observed Stochastic Linear Time-Invariant State-Space Systems with Inputs and Sub-Gaussian Noise

    Sep 8, 2026Mihaly Petreczky, Mohamad Al Ahdab, John LethSystem IdentificationStochastic Dynamics

  4. Generalization as a robust performance property of learning-enabled dynamical systems

    Aug 31, 2026Filippo FabianiGeneralization BoundsLyapunov Function

  5. Deciding When to Switch: E-Processes for Adaptive Minimax Training for Generative Adversarial Nets

    Aug 10, 2026Hyunjoo Kim, Sicheng Wu, Agastya Venkatraman +2Generative Adversarial NetworkEarly Stopping

  6. GenTrack3: Hybrid Stochastic-Deterministic Online Multi-Object Tracking with Cluster-Aware Association

    Aug 10, 2026Toan Van Nguyen, Rasmus G. K. Christiansen, Dirk Kraft +1Multi-Object TrackingMotion Model

  7. Optimal Learning Under Tsybakov Noise

    Aug 9, 2026Steve Hanneke, Hongao Wang, Mingyue XuOptimal LearnerNoisy Labels

  8. Finite Constant Frontiers and Auditable Regret Certificates for Average-Reward Reinforcement Learning

    Aug 7, 2026Ibne Farabi Shihab, Abu Sa-Adat Mohamed Moon-Im Al Ahsan, Md Najmus SwaqeebMarkov Decision ProcessesOptimal Learner

  9. Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions

    Aug 6, 2026Yuepeng Yang, Yuxin Chen, Yuejie ChiMarkov Decision ProcessesOptimal Policies

  10. Optimal Rates for Learning with Monotone Adversaries

    Aug 6, 2026Anay MehrotraOptimal Sample ComplexityOptimal Learner

  11. Learning Ergodic Dynamical Systems from a Finite Trajectory

    Jul 24, 2026Oleksii Kachaiev, Silvia Villa, Lorenzo RosascoStochastic DynamicsOptimal Learner

  12. Mixing-Free and Signal-Optimal Learning of Gaussian Graphical Models from Glauber Dynamics

    Jul 20, 2026Vignesh Tirukkonda, Gautam DasarathyGaussian Mixture Models3D Gaussian Splatting

  13. Provably Optimal Learning Algorithms for Assistance Games

    Jul 9, 2026Nivasini Ananthakrishnan, Mark Bedaywi, Michael I. Jordan +2Optimal LearnerPlan Regret

  14. Neural-ESO: A Dual-Pathway Architecture for Provably Robust Learning-Based Control

    Jul 7, 2026Fan Zhang, Richie Suganda, Jinfeng Chen +4Feedback LinearizationLyapunov Function

  15. Deep Learning for Dynamic Programming with Recursive Utility

    Jul 5, 2026Xianhua Peng, Wu GuoValue FunctionsOptimal Learner

  16. Data Augmentation: A Fourier Analysis Perspective

    Jun 23, 2026Behrooz Tahmasebi, Melanie Weber, Stefanie JegelkaData AugmentationInvariance

  17. Clipping the Price of Adaptivity at the Tail

    Jun 21, 2026Itai Kreisler, Yair Carmon, Oliver HinderConvex OptimizationOptimal Learner

  18. Deep Reinforcement Learning for Minimum Zero-Forcing Sets

    Jun 16, 2026Steve Halley, Maurício GruppiMaximum Independent SetGraph Learning

  19. No-Free-Fairness: Fundamental Limits and Trade-offs in Learning Systems

    Jun 16, 2026Khoat ThanSubgroup InformationOptimal Learner

  20. Optimal Hidden-Target Learning for Online Inventory Optimization on General Convex Sets

    Jun 12, 2026Anthony Pineci, Yunzong XuMonotonic Inventory EstimationConvex Optimization

  21. Majority-of-Three is Optimal

    Jun 11, 2026Divit Rawal, Nikita ZhivotovskiyOptimal LearnerMulticlass Classification

  22. Performance Evaluation of Social Learning

    Jun 8, 2026Felice Scala, Marco Carpentiero, Vincenzo Matta +1Equal Error RateOptimal Learner

  23. Your GFlowNet Secretly Learns an Optimal Transport Plan

    Jun 4, 2026Ian Maksimov, Nikita Morozov, Denis Belomestny +1Generative Flow NetworksOptimal Transport

  24. The price of multi-group transductive learning

    Jun 3, 2026Noah Bergam, Samuel Deng, Daniel HsuTransductive Active LabelingMulticlass Classification

  25. Bayes-Sufficient Representations in Supervised Learning

    Jun 2, 2026Vasileios SevetlidisBayesian Inference ApproachesSupervised Learning

  26. A Tight Theory of Error Feedback Algorithms in Distributed Optimization

    May 29, 2026Daniel Berg Thomsen, Adrien Taylor, Aymeric DieuleveutOptimization Convergence AnalysisOptimal Learner

  27. Non-Asymptotic Convergence of Stochastic Iterative Algorithms: A Lyapunov Framework

    May 29, 2026Zaiwei Chen, Siva Theja MaguluriStochastic ApproximationFinite Time Analysis

  28. LLM-ALSO: LLM-Driven Adaptive Learning-Signal Optimization for Multi-Agent Reinforcement Learning

    May 28, 2026Xiaoguang Wu, Zhi Zheng, Hui XiongMulti-Agent Reinforcement LearningMulti-Agent Large Language Model Systems

  29. Deep-layer limit and stability analysis of the basic forward-backward-splitting induced network (II): learning problems

    May 26, 2026Xuan Lin, Chunlin WuOptimization Convergence AnalysisOptimal Learner

  30. Globally Optimal Training of Spiking Neural Networks via Parameter Reconstruction

    May 8, 2026Himanshu Udupi, Xiaocong Yang, ChengXiang ZhaiSpiking Neural NetworksRecurrent Neural Networks

  31. Almost Sure Convergence Rates of Stochastic Approximation and Reinforcement Learning via a Poisson-Moreau Drift

    May 8, 2026Xinyu Liu, Zixuan Xie, Shangtong ZhangStochastic ApproximationQ-Learning

  32. Distributionally-Robust Learning to Optimize

    May 7, 2026Vinit Ranjan, Jisun Park, Bartolomeo StellatoOptimal LearnerConvex Optimization

  33. Dueling DDQN-Based Adaptive Multi-Objective Handover Optimization for LEO Satellite Networks

    May 4, 2026Po-Heng Chou, Chiapin Wang, Chung-Chi Huang +1Low Earth OrbitWireless Resource Allocation

  34. On the Learning Curves of Revenue Maximization

    Apr 29, 2026Steve Hanneke, Alkis Kalavasis, Shay Moran +1Optimal LearnerUtility Maximization

  35. Goal-oriented learning of stochastic differential equations using error bounds on path-space observables

    Mar 20, 2026Joanna Zou, Han Cheng Lie, Youssef MarzoukStochastic Differential EquationsSurrogate Gradient

  36. Convergence Rate of a Functional Learning Method for Contextual Stochastic Optimization

    Mar 13, 2026Noel Smith, Andrzej RuszczynskiStochastic OptimizationOptimal Learner

  37. Relatively Smart: A New Approach for Instance-Optimal Learning

    Mar 2, 2026Shaddin Dughmi, Alireza F. PourSemi-Supervised LearningOptimal Learner

  38. Learning with Monotone Adversarial Corruptions

    Jan 5, 2026Kasper Green Larsen, Chirag Pabbaraju, Abhishek ShettyAdversarial TransferabilityOptimal Learner

  39. A statistical physics framework for optimal learning

    Jul 10, 2025Francesca Mignacco, Francesco MoriOptimal LearnerStochastic Gradient Descent