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Online Learning

1012 directly classified papers

Papers per year

Papers

Regret Bounds for Adaptive Nonlinear Control L4DC 2021
MetaGrad: Adaptation using Multiple Learning Rates in Online Learning JMLR 2021
Learning Whenever Learning is Possible: Universal Learning under General Stochastic Processes JMLR 2021
Joint Online Learning and Decision-making via Dual Mirror Descent ICML 2021
Projection-free Decentralized Online Learning for Submodular Maximization over Time-Varying Networks JMLR 2021
A Contextual Bandit Bake-off JMLR 2021
Gaussian Process-Based Real-Time Learning for Safety Critical Applications ICML 2021
Prediction against a limited adversary JMLR 2021
Mean Field Equilibrium in Multi-Armed Bandit Game with Continuous Reward IJCAI 2021
Message Passing Adaptive Resonance Theory for Online Active Semi-supervised Learning ICML 2021
Network Inference and Influence Maximization from Samples ICML 2021
Dynamic Balancing for Model Selection in Bandits and RL ICML 2021
Online Continual Learning With Natural Distribution Shifts: An Empirical Study With Visual Data ICCV 2021
Minimax Optimal Quantile and Semi-Adversarial Regret via Root-Logarithmic Regularizers NIPS 2021
Dual Adaptivity: A Universal Algorithm for Minimizing the Adaptive Regret of Convex Functions NIPS 2021
Revisiting Projection-free Online Learning: the Strongly Convex Case AISTATS 2021
Tracking Regret Bounds for Online Submodular Optimization AISTATS 2021
Gaming Helps! Learning from Strategic Interactions in Natural Dynamics AISTATS 2021
Fast rates for prediction with limited expert advice NIPS 2021
Mixability made efficient: Fast online multiclass logistic regression NIPS 2021
Lenient Regret and Good-Action Identification in Gaussian Process Bandits ICML 2021
Design of Experiments for Stochastic Contextual Linear Bandits NIPS 2021
Online Learning with Optimism and Delay ICML 2021
Online Active Learning with Surrogate Loss Functions NIPS 2021
Stochastic Online Linear Regression: the Forward Algorithm to Replace Ridge NIPS 2021