Stochastic Optimization

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Overview

Stochastic optimization seeks good decisions when exact objectives or gradients are unavailable, observations are noisy, or the environment changes, making it central to machine learning, planning, and resource allocation. Common approaches include stochastic gradient descent and adaptive optimizers, variance reduction, mirror and proximal methods, and online or bandit algorithms; robust and risk-sensitive methods address heavy-tailed noise and costly failures. Researchers evaluate these methods through convergence, sample-complexity, and regret guarantees, as well as experiments in deep-model training, constrained planning, and simulation. A continuing challenge is to make guarantees hold under realistic noise, dependence, and changing data while keeping computation, communication, and tuning costs manageable.

Latest papers

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210 papers34 papers in the last four weeks, up 70% on the four weeks before. 0.2% of all new papers.

  1. Stein Variational Black-Box Combinatorial Optimization

    Apr 17, 2026Thomas Landais, Olivier Goudet, Adrien Goëffon +2Stochastic OptimizationBlack-Box Optimization

    LERIA, Université d’Angers, 2 Boulevard Lavoisier, Angers 49045, France

  2. StoSignSGD: Unbiased Structural Stochasticity Fixes SignSGD for Training Large Language Models

    Apr 16, 2026Dingzhi Yu, Rui Pan, Yuxing Liu +1Stochastic OptimizationSign-Based Optimization

    University of Illinois Urbana-Champaign

  3. CLion: Efficient Cautious Lion Optimizer with Enhanced Generalization

    Apr 16, 2026Feihu Huang, Guanyi Zhang, Songcan ChenStochastic OptimizationSign-Based Optimization

    College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China · MIIT Key Laboratory of Pattern Analysis and Machine Intelligence, Nanjing, China

  4. Multistage Conditional Compositional Optimization

    Apr 15, 2026Buse Şen, Yifan Hu, Daniel KuhnStochastic OptimizationDecision-Making under Uncertainty

    EPFL, Switzerland · Rutgers University, USA

  5. Greedy Approaches for Packing While Travelling with Deterministic and Stochastic Constraints

    Apr 15, 2026Thilina Pathirage Don, Aneta Neumann, Frank NeumannGreedy OptimizationCombinatorial Optimization

    Optimisation and Logistics, School of Computer Science and Information Technology, Adelaide University, Adelaide, Australia

  6. On the use of evolutionary optimization for the dynamic chance constrained open-pit mine scheduling problem

    Apr 15, 2026Ishara Hewa Pathiranage, Aneta NeumannStochastic OptimizationChance-Constrained Optimization

    Machine Learning and Optimisation, School of Computer Science and Information Technology, Adelaide University, Adelaide, Australia

  7. Classical and Quantum Speedups for Non-Convex Optimization via Energy Conserving Descent

    Apr 14, 2026Yihang Sun, Huaijin Wang, Patrick Hayden +1Nonconvex OptimizationGlobal Optimization

    Department of Management Science and Engineering, Stanford University. · Leinweber Institute for Theoretical Physics, Stanford University. · Leinweber Institute for Theoretical Physics, Stanford University and Google DeepMind.

  8. Obtaining Partition Crossover masks using Statistical Linkage Learning for solving noised optimization problems with hidden variable dependency structure

    Apr 13, 2026M. W. Przewozniczek, B. Frej, M. M. Komarnicki +2Evolutionary OptimizationBlack-Box Optimization

    Wroclaw Univ. of Science and Techn. Wroclaw, Poland · University of São Paulo Ribeirão Preto, Brazil

  9. Last-Iterate Convergence of Randomized Kaczmarz and SGD with Greedy Step Size

    Apr 10, 2026Michał Dereziński, Xiaoyu DongLast-Iterate ConvergenceStochastic Optimization

    University of Michigan · National University of Singapore

  10. Offline Local Search for Online Stochastic Bandits

    Apr 10, 2026Gerdus Benadè, Rathish Das, Thomas LavastidaCombinatorial Multi-Armed BanditsStochastic Optimization

    Boston University, MA, USA. · University of Houston, TX, USA. · University of Texas at Dallas, TX, USA.

  11. Analysis of Search Heuristics in the Multi-Armed Bandit Setting

    Apr 9, 2026Jasmin Brandt, Barbara Hammer, Timo Kötzing +1Dueling BanditsMulti-Armed Bandits

    University of Bielefeld Bielefeld, Germany · Hasso Plattner Institute University of Potsdam Potsdam, Germany

  12. Anytime Analysis on BinVal: Adaptive Parameters Help

    Apr 8, 2026Timo Kötzing, Jurek SanderRuntime Analysis of Evolutionary AlgorithmsEvolutionary Optimization

    Hasso Plattner Institute University of Potsdam Potsdam, Germany

  13. Stochastic Auto-conditioned Fast Gradient Methods with Optimal Rates

    Apr 7, 2026Yao Ji, Guanghui LanStochastic OptimizationAccelerated Gradient Methods

    H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, 225 North Ave, Atlanta, GA 30332, USA

  14. Optimizing Service Operations via LLM-Powered Multi-Agent Simulation

    Apr 6, 2026Yanyuan Wang, Xiaowei ZhangStochastic OptimizationDecision-Making under Uncertainty

    Department of Industrial Engineering and Decision Analytics, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong SAR

  15. Finite-time analysis of Multi-timescale Stochastic Optimization Algorithms

    Mar 31, 2026Kaustubh Kartikey, Shalabh BhatnagarStochastic OptimizationStochastic Optimization Convergence

  16. Adaptive decision-making for stochastic service network design

    Mar 25, 2026Javier Durán-Micco, Bilge AtasoyStochastic OptimizationMetaheuristic Optimization

    Maritime and Transport Technology (MTT), Mechanical Engineering (ME), Delft University of Technology/ Mekelweg 2, 2628CD, Delft, The Netherlands.

  17. On the Role of Batch Size in Stochastic Conditional Gradient Methods

    Mar 22, 2026Rustem Islamov, Roman Machacek, Aurelien Lucchi +3Stochastic OptimizationNeural Network Optimization

    University of Basel, Switzerland · MBZUAI, UAE · University of Bern, Switzerland +2

  18. Uniform a priori bounds and error analysis for the Adam stochastic gradient descent optimization method

    Mar 19, 2026Steffen Dereich, Thang Do, Arnulf JentzenStochastic OptimizationStochastic Optimization Convergence

    Institute for Mathematical Stochastics, Faculty of Mathematics and Computer Science, University of Münster, Germany · School of Data Science, The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen), China · Department of Probability and Statistic, Institute of Mathematics, Vietnam Academy of Science and Technology, Vietnam +2

  19. Stochastic set-valued optimization and its application to robust learning

    Mar 18, 2026Tommaso Giovannelli, Jingfu Tan, Luis Nunes VicenteStochastic OptimizationDistribution Shift Robustness

    Department of Mechanical and Materials Engineering, University of Cincinnati, Cincinnati, OH 45221, USA · Department of Industrial and Systems Engineering, Lehigh University, Bethlehem, PA 18015-1582, USA

  20. Shuffling the Stochastic Mirror Descent via Dual Lipschitz Continuity and Kernel Conditioning

    Mar 17, 2026Junwen Qiu, Leilei Mei, Junyu ZhangRandom ReshufflingStochastic Optimization

    Industrial Systems Engineering and Management, National University of Singapore

  21. Unbiased and Biased Variance-Reduced Forward-Reflected-Backward Splitting Methods for Stochastic Composite Inclusions

    Mar 16, 2026Quoc Tran-Dinh, Nghia Nguyen-TrungStochastic OptimizationStochastic Optimization Convergence

    Department of Statistics and Operations Research The University of North Carolina at Chapel Hill 318 Hanes Hall, UNC-Chapel Hill, NC 27599-3260.

  22. POLCA: Stochastic Generative Optimization with LLM

    Mar 16, 2026Xuanfei Ren, Allen Nie, Tengyang Xie +1Large Language Model-Guided OptimizationStochastic Optimization

    University of Wisconsin-Madison, Madison, WI · Google DeepMind, Mountain View, CA · Google Research, Kirkland, WA

  23. Probabilistic Gaussian Homotopy: A Probability-Space Continuation Framework for Nonconvex Optimization

    Mar 13, 2026Eshed Gal, Samy Wu Fung, Eldad HaberNonconvex OptimizationStochastic Optimization

    University of British Columbia, Vancouver, BC, Canada · Colorado School of Mines, Golden, CO, USA

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

    Mar 13, 2026Noel Smith, Andrzej RuszczynskiStochastic OptimizationStochastic Approximation

    Department of Management Science and Information Systems, Rutgers University

  25. Adaptive Conditional Residual Sampling for Spectral Risk Optimisation under Decision-Dependent Uncertainty

    Mar 12, 2026Marcell T. KurbuczStochastic OptimizationDecision-Making under Uncertainty

    Institute for Global Prosperity, The Bartlett, University College London, 9–11 Endsleigh Gardens, London, WC1H 0EH, United Kingdom

  26. A Trust-Region Interior-Point Stochastic Sequential Quadratic Programming Method

    Mar 10, 2026Yuchen Fang, Jihun Kim, Sen Na +2Constrained OptimizationStochastic Optimization

    Department of Mathematics, University of California, Berkeley · Department of IEOR, University of California, Berkeley · School of Industrial and Systems Engineering, Georgia Tech +1

  27. Stabilizing Bandits using Regularization: Precise Regret and A Quantitative Central Limit Theorem

    Mar 10, 2026Budhaditya Halder, Ishan Sengupta, Koustav Chowdhury +2Multi-Armed BanditsAlgorithmic Stability

    Department of Statistics, Rutgers University · Indian Statistical Institute, Kolkata

  28. OptEMA: Adaptive Exponential Moving Average for Stochastic Optimization with Zero-Noise Optimality

    Mar 10, 2026Ganzhao YuanStochastic OptimizationAdaptive Gradient Methods

    Shenzhen University of Advanced Technology (SUAT), China

  29. Multi-Objective Evolutionary Optimization of Chance-Constrained Multiple-Choice Knapsack Problems with Implicit Probability Distributions

    Mar 9, 2026Xuanfeng Li, Shengcai Liu, Wenjie Chen +2Chance-Constrained OptimizationCombinatorial Optimization

    Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation, Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China · School of Information Management, Central China Normal University, Wuhan 430079, China · Centre for Frontier AI Research, Institute of High Performance Computing, Agency for Science Technology and Research, Singapore 138632 +1

  30. Adaptive Lipschitz-Free Conditional Gradient Methods for Stochastic Composite Nonconvex Optimization

    Mar 6, 2026Ganzhao YuanNonconvex Stochastic OptimizationStochastic Optimization

    Shenzhen University of Advanced Technology (SUAT), China