Online Learning

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Overview

Online learning studies how to make predictions and decisions as data arrive, rather than training once on a fixed dataset. Common approaches include Online Mirror Descent and Follow-the-Regularized-Leader for optimization, exponential-weights methods for choosing among experts, and bandit algorithms when feedback is limited. Researchers analyze regret and mistake bounds in adversarial, stochastic, and changing environments, and apply these methods to areas such as forecasting, auctions, and resource allocation. A central challenge is adapting quickly to change while remaining stable and efficient when feedback is delayed, noisy, or costly.

Latest papers

CardsList

131 papers24 papers in the last four weeks, up 60% on the four weeks before. 0.1% of all new papers.

  1. Batched NN 4D-Var: a performant hybrid model framework for the Integrated Forecasting System

    Oct 23, 2026Alban Farchi, Marcin Chrust, Massimo Bonavita +3Weather ForecastingData Assimilation

    ECMWF Bonn, Germany · ECMWF Reading, United Kingdom · CEREA, ENPC, EDF R&D Institut Polytechnique de Paris Île–de–France, France

  2. A Simple and Unified Method for Gradient-Variation Regret

    Oct 19, 2026Hang Yu, Peng ZhaoOnline LearningDynamic Regret Minimization

    State Key Laboratory for Novel Software Technology, Nanjing University, China · School of Artificial Intelligence, Nanjing University, China

  3. No-Regret Language Generation

    Oct 16, 2026Jiaxun Li, Vinod Raman, Ambuj TewariText GenerationMinimax Regret

    Department of Statistics, University of Michigan

  4. Learning Changes the World and Then What Was Learned has Changed: Training and Deploying Neural Networks in the Control Loop

    Oct 15, 2026Vittorio LippiDistribution ShiftFeedback Control

    Calejo Hybrid Intelligence AB, Mellansjö 109, 92592 Tärnaby, Sweden

  5. Online Quantile Omniprediction for Proper Losses

    Oct 15, 2026Hyunsuk Kim, Isaac Gibbs, Michael W. Mahoney +1Probabilistic ForecastingQuantile Regression

    Department of Statistics, University of California, Berkeley · Department of Statistics, University of Toronto · ICSI, LBNL, and Dept. of Statistics, University of California, Berkeley

  6. Longitudinal Learner Participation Profiling in Online Learning: Heterogeneous Consensus Clustering under Unequal Observation Windows

    Oct 12, 2026David Otoo-Arthur, Terence L. van ZylEducational Data MiningClustering

    University of the Witwatersrand, Johannesburg, South Africa · University of Johannesburg, Johannesburg, South Africa

  7. A Time-Synchronous Prequential Evaluation Framework for Next-Week Student Disengagement Prediction from Moodle LMS Logs

    Oct 12, 2026David Otoo-Arthur, Terence L. van ZylEarly Warning DetectionEducational Data Mining

    University of the Witwatersrand, Johannesburg, South Africa · University of Johannesburg, Johannesburg, South Africa

  8. To Defer or Not to Defer? Online Learning with LLMs and Congested Experts

    Oct 10, 2026Vasileios Saketos, William Reveillard, Alexandre Proutiere +2Learning to DeferOnline Learning

    KTH Royal Institute of Technology, Stockholm, Sweden

  9. Conformal Sequential Decision Making With Cost and Sublinear Policy Regret Guarantees

    Oct 10, 2026Jayadev Naram, Giuseppe Durisi, Matteo Zecchin +1Sequential Decision MakingOnline Learning

    Department of Electrical Engineering, Chalmers University of Technology, 412 96 Göteborg, Sweden · Communication Systems Department, EURECOM, 06410 Sophia Antipolis, France · Institute for Intelligent Networked Systems (INSI), Northeastern University London, E1W 1LP London, UK

  10. Prediction Is Not a Sufficient Memory State

    Oct 9, 2026Robert Jenkinson AlvarezOnline Learning

  11. Simultaneous Competitive and Regret Guarantees for TCP Acknowledgment

    Oct 9, 2026Tsubasa Harada, Yasushi Kawase, Hanna SumitaMinimax RegretOnline Learning

    Institute of Science Tokyo · Chuo University

  12. Beyond Second-Order Information: Paid Logistic Regression with Noisy Features

    Oct 9, 2026Sanghwa Kim, Kyoungseok Jang, Se-Young YunOnline LearningLogistic Regression

    Kim Jaechul Graduate School of AI, KAIST Seoul 02455, Republic of Korea · Department of AI, Chung-Ang University Soeul 06974, Republic of Korea

  13. AdaptLSTM: Efficient Adaptive Online Learning for Cloud Workload Forecasting under Distribution Drift

    Oct 8, 2026Xinhua Miao, Bowei Yang, Zhengong CaiOnline LearningAdaptive Learning

    Zhejiang University, Ningbo, China · Zhejiang University, Hangzhou, China

  14. Optimally Pacing Budget Spending and Learning

    Oct 8, 2026Mark Braverman, Jingyi Liu, Jieming Mao +2Online LearningOnline Resource Allocation

    Department of Computer Science, Princeton University · Google Research

  15. Evolve on the Host, Predict on the Edge: Deploying Online Neuroevolutionary Architecture Search for Cross-sectional Stock Return Prediction

    Oct 7, 2026Jonathan Chang, Zimeng LyuStock Price ForecastingTime Series Forecasting

    Union County Magnet High School · Department of Computer Science and Technology, Kean University

  16. sHAIL-Causal: A Sequential Staircase Procedure for Invariant Causal Predictor Discovery

    Oct 5, 2026Ernest FokouéCausal DiscoveryCausal Inference

    School of Mathematics and Statistics, Rochester Institute of Technology

  17. AdaSpark: Adaptive DSpark with Online Learning for Tree Verification and N-gram Fill

    Oct 5, 2026Liquan Liu, Yifan Zhang, Bowei XuLLM Inference SchedulingSpeculative Decoding

    Zeraix

  18. Understanding Generative AI Use in Programming MOOCs: The Role of Course Context and Learner Characteristics

    Oct 3, 2026Marina LeppGenerative AI in EducationProgramming Education

    Institute of Computer Science University of Tartu Tartu, Estonia

  19. Online Verification of Language Model Responses Under Cost Constraints

    Oct 2, 2026Erfan Hajihashemi, Yanning ShenLLM ReliabilityOnline Learning

    Department of Electrical Engineering & Computer Science University of California, Irvine

  20. Participation-Sensitive Convergence and the Fragment First, Converge Later Pattern in Asynchronous Online Learning: A Topological Analysis Across 22 OULAD Courses

    Oct 1, 2026Hitoshi Inoue, Koichi YasutakeEducational Data MiningOnline Learning

    Nakamura Gakuen University, Japan · Hiroshima University, Japan

  21. Towards a Cloud Fog Edge System for Smart Building

    Oct 1, 2026Christophe Cérin, Mamadou Sow, Frédéric AndrèsOn-Device TrainingEdge ML

    University Sorbonne Paris Nord LIPN, UMR CNRS 7030 INRIA DATAMOVE Paris/Grenoble, France · University Sorbonne Paris Nord LIPN, UMR CNRS 7030 Villetaneuse, France · National institute of Informatics 2 Chome-1-2 Hitotsubashi, Chiyoda City, Tokyo 101-8430, Japan

  22. LARC: Low-Rank Adaptive Residual Connections for Learning in Frozen Models

    Sep 30, 2026Junyi Zou, Avrova DonzMeta-LearningResidual Learning

    MMLA-org · Communication University of China (CUC), No. 1 Dingfuzhuang East Street, Chaoyang District, Beijing 100024, China

  23. When Is Coarse Supervision Worth It? Cost-Aware Learning under Unknown Aggregation

    Sep 29, 2026Jianyu Xu, Smriti Jha, Aarti Singh +1Cost-Sensitive LearningStatistical Learning Theory

    University of North Carolina at Charlotte, Charlotte, NC 28223 · Carnegie Mellon University, Pittsburgh, PA 15213

  24. Improving scalable oversight with co-trained monitors

    Sep 28, 2026Joseph H. Rudoler, Kevin Tan, Benedict Tessler +2Scalable OversightAdversarial Robustness

    University of Pennsylvania

  25. Evasion Attacks on Cost-Utility-Based Adversarial Training for Online AutoML in IoT Networks

    Sep 25, 2026Chukwunonso Henry Nwokoye, Wajiha Zaheer, Khalil El-Khatib +1Adversarial RobustnessAdversarial Training

    Faculty of Business and Information Technology, Ontario Tech University, Oshawa, Ontario, Canada · Department of Computer Science, Alex Ekwueme Federal University, Nigeria

  26. Online Learning via Learned Latent Bayesian Tracking

    Sep 25, 2026Guy Gerson, Tomer Raviv, Nir Shlezinger +2Online LearningBayesian Filtering

    School of ECE Ben-Gurion University Be‘er-Sheva, Israel · Institute for Intelligent Networked Systems (INSI) Northeastern University London London, U.K

  27. Downside-Controlled Online Forecast Combination under Delayed and Revised Outcomes

    Sep 24, 2026Minkyoung Kim, Hyunjung Byun, Yohan Lee +1Time Series ForecastingOnline Learning

    Graduate School of Information, Yonsei University, Seoul, 03722, South Korea

  28. Full-Covariance Smoothing of Bayesian Neural Networks for Online Adaptation

    Sep 23, 2026Oren Wright, Haoming Jing, Qiaoan Shen +3Bayesian Neural NetworksBayesian Filtering

    Department of Electrical and Computer Engineering, Carnegie Mellon University · Software Engineering Institute, Carnegie Mellon University · Fujitsu Research of America

  29. Optimal Randomized Proper Online Learning

    Sep 18, 2026Zachary Chase, Idan MehalelOnline LearningStatistical Learning Theory

    Rutgers University · The Hebrew University

  30. Online Adaptive Kernel Mixing for Gaussian Process Decision Making

    Sep 17, 2026Kavin Aravindan, Mani Tej Sriram, Gautam Dasarathy +1Bayesian OptimizationActive Learning

    International Institute of Information Technology, Hyderabad · Arizona State University