conftrace_

regret bound

1926 papers

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RB

Co-occurring keywords

online learning (1777) multi-armed bandit (1098) contextual bandit (381) stochastic optimization (1060) reinforcement learning (4352) online algorithm (445) upper confidence bound (197) markov decision process (790) thompson sampling (237) online convex optimization (165)

Papers

Minimax Time Series Prediction NIPS 2015
Explore no more: Improved high-probability regret bounds for non-stochastic bandits NIPS 2015
Non-Asymptotic Analysis of a New Bandit Algorithm for Semi-Bounded Rewards JMLR 2015
Second-Order Non-Stationary Online Learning for Regression JMLR 2015
Tight Regret Bounds for Stochastic Combinatorial Semi-Bandits AISTATS 2015
Online Optimization : Competing with Dynamic Comparators AISTATS 2015
Global Multi-armed Bandits with Hölder Continuity AISTATS 2015
On the Complexity of Bandit Linear Optimization COLT 2015
Exp-Concavity of Proper Composite Losses COLT 2015
Thompson Sampling for Learning Parameterized Markov Decision Processes COLT 2015
Hierarchies of Relaxations for Online Prediction Problems with Evolving Constraints COLT 2015
Batched Bandit Problems COLT 2015
First-order regret bounds for combinatorial semi-bandits COLT 2015
Online Density Estimation of Bradley-Terry Models COLT 2015
Online Learning for Adversaries with Memory: Price of Past Mistakes NIPS 2015
Fighting Bandits with a New Kind of Smoothness NIPS 2015
Revenue Optimization against Strategic Buyers NIPS 2015
Cornering Stationary and Restless Mixing Bandits with Remix-UCB NIPS 2015
The Pareto Regret Frontier for Bandits NIPS 2015
Bandits with Unobserved Confounders: A Causal Approach NIPS 2015
Achieving All with No Parameters: AdaNormalHedge COLT 2015
Regret Lower Bound and Optimal Algorithm in Dueling Bandit Problem COLT 2015
A Chaining Algorithm for Online Nonparametric Regression COLT 2015
Contextual Dueling Bandits COLT 2015
On-Line Learning Algorithms for Path Experts with Non-Additive Losses COLT 2015