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Online Algorithms

2190 directly classified papers

Papers per year

Papers

Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient ICML 2016
Regret Analysis of the Finite-Horizon Gittins Index Strategy for Multi-Armed Bandits COLT 2016
Linear Contextual Bandits with Knapsacks NIPS 2016
Threshold Bandits, With and Without Censored Feedback NIPS 2016
Optimistic Gittins Indices NIPS 2016
On Explore-Then-Commit strategies NIPS 2016
Improved Regret Bounds for Oracle-Based Adversarial Contextual Bandits NIPS 2016
Phased Exploration with Greedy Exploitation in Stochastic Combinatorial Partial Monitoring Games NIPS 2016
(Bandit) Convex Optimization with Biased Noisy Gradient Oracles AISTATS 2016
Adaptive Concentration Inequalities for Sequential Decision Problems NIPS 2016
Multi-scale exploration of convex functions and bandit convex optimization COLT 2016
Optimistic Bandit Convex Optimization NIPS 2016
Online Isotonic Regression COLT 2016
Online Collaborative Learning for Open-Vocabulary Visual Classifiers CVPR 2016
The Multi-fidelity Multi-armed Bandit NIPS 2016
Shifting Regret, Mirror Descent, and Matrices ICML 2016
No-Regret Algorithms for Heavy-Tailed Linear Bandits ICML 2016
Contextual semibandits via supervised learning oracles NIPS 2016
Multiple-Play Bandits in the Position-Based Model NIPS 2016
Online learning in repeated auctions COLT 2016
Instance-dependent Regret Bounds for Dueling Bandits COLT 2016
Highly-Smooth Zero-th Order Online Optimization COLT 2016
An efficient algorithm for contextual bandits with knapsacks, and an extension to concave objectives COLT 2016
Double Thompson Sampling for Dueling Bandits NIPS 2016
A Closer Look at Adaptive Regret JMLR 2016