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online learning

1770 papers

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Also known as

OLO OL

Co-occurring keywords

regret bound (1918) multi-armed bandit (1091) stochastic optimization (1060) regret minimization (315) contextual bandit (379) reinforcement learning (4122) online algorithm (444) convex optimization (1320) adversarial learning (1592) continual learning (1164)

Papers

Learning in Non-convex Games with an Optimization Oracle COLT 2019
An Information-Theoretic Approach to Minimax Regret in Partial Monitoring COLT 2019
Equipping Experts/Bandits with Long-term Memory NIPS 2019
Dynamic Local Regret for Non-convex Online Forecasting NIPS 2019
Equal Opportunity in Online Classification with Partial Feedback NIPS 2019
Nonstochastic Multiarmed Bandits with Unrestricted Delays NIPS 2019
Generalize Across Tasks: Efficient Algorithms for Linear Representation Learning ALT 2019
Online Prediction of Switching Graph Labelings with Cluster Specialists NIPS 2019
Bandit Multiclass Linear Classification: Efficient Algorithms for the Separable Case ICML 2019
Dynamic Learning with Frequent New Product Launches: A Sequential Multinomial Logit Bandit Problem ICML 2019
Learning Linear-Quadratic Regulators Efficiently with only $\sqrtT$ Regret ICML 2019
Online Learning with Sleeping Experts and Feedback Graphs ICML 2019
Anytime Online-to-Batch, Optimism and Acceleration ICML 2019
Adaptive Scale-Invariant Online Algorithms for Learning Linear Models ICML 2019
Online Learning to Rank with Features ICML 2019
Cautious Regret Minimization: Online Optimization with Long-Term Budget Constraints ICML 2019
Learning from Delayed Outcomes via Proxies with Applications to Recommender Systems ICML 2019
Adversarial Online Learning with noise ICML 2019
Contextual Memory Trees ICML 2019
Online Adaptive Principal Component Analysis and Its extensions ICML 2019
Beating Stochastic and Adversarial Semi-bandits Optimally and Simultaneously ICML 2019
Efficient online learning with kernels for adversarial large scale problems NIPS 2019
Online-Within-Online Meta-Learning NIPS 2019
Partially Observable Multi-Sensor Sequential Change Detection: A Combinatorial Multi-Armed Bandit Approach AAAI 2019
Leveraging Observations in Bandits: Between Risks and Benefits AAAI 2019