multi-armed bandit

Efficient learning by implicit exploration in bandit problems with side observations NeurIPS 2014 Efficient Partial Monitoring with Prior Information NeurIPS 2014 Extreme bandits NeurIPS 2014 Finding a most biased coin with fewest flips COLT 2014 Latent Bandits. ICML 2014 Learning Multiple Tasks in Parallel with a Shared Annotator NeurIPS 2014 Learning to Optimize via Information-Directed Sampling NeurIPS 2014 lil’ UCB : An Optimal Exploration Algorithm for Multi-Armed Bandits COLT 2014 Lipschitz Bandits: Regret Lower Bound and Optimal Algorithms COLT 2014 Most Correlated Arms Identification COLT 2014 Multiarmed Bandits With Limited Expert Advice COLT 2014 On correlation and budget constraints in model-based bandit optimization with application to automatic machine learning AISTATS 2014 One Practical Algorithm for Both Stochastic and Adversarial Bandits ICML 2014 Online Clustering of Bandits ICML 2014 Online combinatorial optimization with stochastic decision sets and adversarial losses NeurIPS 2014 Open Problem: Shifting Experts on Easy Data COLT 2014 Optimality of Thompson Sampling for Gaussian Bandits Depends on Priors AISTATS 2014 Optimal PAC Multiple Arm Identification with Applications to Crowdsourcing ICML 2014 Optimal Regret Minimization in Posted-Price Auctions with Strategic Buyers NeurIPS 2014 Prediction with Limited Advice and Multiarmed Bandits with Paid Observations ICML 2014 Reducing Dueling Bandits to Cardinal Bandits ICML 2014 Spectral Bandits for Smooth Graph Functions ICML 2014 Stochastic Multi-Armed-Bandit Problem with Non-stationary Rewards NeurIPS 2014 Stochastic Regret Minimization via Thompson Sampling COLT 2014 The Blinded Bandit: Learning with Adaptive Feedback NeurIPS 2014