conftrace_

multi-armed bandit

1098 papers

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Also known as

MAB

Co-occurring keywords

regret bound (1926) online learning (1777) stochastic optimization (1060) thompson sampling (237) upper confidence bound (197) regret minimization (315) online algorithm (445) sample complexity (1169) contextual bandit (381) best arm identification (85)

Papers

Cornering Stationary and Restless Mixing Bandits with Remix-UCB NIPS 2015
Linear Multi-Resource Allocation with Semi-Bandit Feedback NIPS 2015
Online Learning with Gaussian Payoffs and Side Observations NIPS 2015
Explore no more: Improved high-probability regret bounds for non-stochastic bandits NIPS 2015
Efficient Thompson Sampling for Online Matrix-Factorization Recommendation NIPS 2015
Budgeted Bandit Problems with Continuous Random Costs ACML 2015
Online Learning with Feedback Graphs: Beyond Bandits COLT 2015
On Identifying Good Options under Combinatorially Structured Feedback in Finite Noisy Environments ICML 2015
Non-Asymptotic Analysis of a New Bandit Algorithm for Semi-Bounded Rewards JMLR 2015
Regret Lower Bound and Optimal Algorithm in Finite Stochastic Partial Monitoring NIPS 2015
Cheap Bandits ICML 2015
On Top-k Selection in Multi-Armed Bandits and Hidden Bipartite Graphs NIPS 2015
Bandits with Unobserved Confounders: A Causal Approach NIPS 2015
The Pareto Regret Frontier for Bandits NIPS 2015
Stochastic Online Greedy Learning with Semi-bandit Feedbacks NIPS 2015
Fighting Bandits with a New Kind of Smoothness NIPS 2015
Adaptive Strategy for Stratified Monte Carlo Sampling JMLR 2015
Batched Bandit Problems COLT 2015
High Dimensional Bayesian Optimisation and Bandits via Additive Models ICML 2015
Global Multi-armed Bandits with Hölder Continuity AISTATS 2015
Reactive bandits with attitude AISTATS 2015
Efficient Learning in Large-Scale Combinatorial Semi-Bandits ICML 2015
Simple regret for infinitely many armed bandits ICML 2015
Optimal Regret Analysis of Thompson Sampling in Stochastic Multi-armed Bandit Problem with Multiple Plays ICML 2015
Qualitative Multi-Armed Bandits: A Quantile-Based Approach ICML 2015