conftrace_

regret bound

1926 papers

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Also known as

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

Prediction with Limited Advice and Multiarmed Bandits with Paid Observations ICML 2014
Towards Minimax Online Learning with Unknown Time Horizon ICML 2014
Thompson Sampling for Complex Online Problems ICML 2014
A Drifting-Games Analysis for Online Learning and Applications to Boosting NIPS 2014
One Practical Algorithm for Both Stochastic and Adversarial Bandits ICML 2014
Adaptivity and Optimism: An Improved Exponentiated Gradient Algorithm ICML 2014
Efficient Partial Monitoring with Prior Information NIPS 2014
Follow the Leader with Dropout Perturbations COLT 2014
Online Linear Optimization via Smoothing COLT 2014
Robust Multi-objective Learning with Mentor Feedback COLT 2014
Higher-Order Regret Bounds with Switching Costs COLT 2014
A second-order bound with excess losses COLT 2014
Open Problem: Shifting Experts on Easy Data COLT 2014
Online Learning in Markov Decision Processes with Changing Cost Sequences ICML 2014
Tracking Adversarial Targets ICML 2014
Efficient learning by implicit exploration in bandit problems with side observations NIPS 2014
Surrogate Regret Bounds for Bipartite Ranking via Strongly Proper Losses JMLR 2014
On the Bayes-Optimality of F-Measure Maximizers JMLR 2014
Learning the Learning Rate for Prediction with Expert Advice NIPS 2014
Parallelizing Exploration-Exploitation Tradeoffs in Gaussian Process Bandit Optimization JMLR 2014
On Multilabel Classification and Ranking with Bandit Feedback JMLR 2014
Online combinatorial optimization with stochastic decision sets and adversarial losses NIPS 2014
Bayesian Multi-Scale Optimistic Optimization AISTATS 2014
Unimodal Bandits: Regret Lower Bounds and Optimal Algorithms ICML 2014
The Blinded Bandit: Learning with Adaptive Feedback NIPS 2014