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Online Learning

1012 directly classified papers

Papers per year

Papers

Cascading Non-Stationary Bandits: Online Learning to Rank in the Non-Stationary Cascade Model IJCAI 2019
Improved Algorithm on Online Clustering of Bandits IJCAI 2019
Efficient online learning with kernels for adversarial large scale problems NIPS 2019
Online Forecasting of Total-Variation-bounded Sequences NIPS 2019
On the optimality of the Hedge algorithm in the stochastic regime JMLR 2019
Logarithmic Regret for Online Control NIPS 2019
Private Learning Implies Online Learning: An Efficient Reduction NIPS 2019
Dynamic Learning of Sequential Choice Bandit Problem under Marketing Fatigue AAAI 2019
Online Learning from Data Streams with Varying Feature Spaces AAAI 2019
Preference-Aware Task Assignment in On-Demand Taxi Dispatching: An Online Stable Matching Approach AAAI 2019
Think out of the "Box": Generically-Constrained Asynchronous Composite Optimization and Hedging NIPS 2019
Incorporating Behavioral Constraints in Online AI Systems AAAI 2019
Balanced Linear Contextual Bandits AAAI 2019
Quantifying Uncertainty in Online Regression Forests JMLR 2019
Reducing Exploration of Dying Arms in Mortal Bandits UAI 2019
Equal Opportunity in Online Classification with Partial Feedback NIPS 2019
Nonstochastic Multiarmed Bandits with Unrestricted Delays NIPS 2019
Low-Complexity Nonparametric Bayesian Online Prediction with Universal Guarantees NIPS 2019
Dying Experts: Efficient Algorithms with Optimal Regret Bounds NIPS 2019
Batched Multi-armed Bandits Problem NIPS 2019
BubbleRank: Safe Online Learning to Re-Rank via Implicit Click Feedback UAI 2019
Secretary Ranking with Minimal Inversions NIPS 2019
Censored Semi-Bandits: A Framework for Resource Allocation with Censored Feedback NIPS 2019
Dynamic Trip-Vehicle Dispatch with Scheduled and On-Demand Requests UAI 2019
Large Scale Markov Decision Processes with Changing Rewards NIPS 2019