Online Algorithms

Fundamental Limits of Online and Distributed Algorithms for Statistical Learning and Estimation NeurIPS 2014 Higher-Order Regret Bounds with Switching Costs COLT 2014 Improved Bounds for Online Learning Over the Permutahedron and Other Ranking Polytopes AISTATS 2014 Learning Multiple Tasks in Parallel with a Shared Annotator NeurIPS 2014 Learning the Learning Rate for Prediction with Expert Advice NeurIPS 2014 Learning to Optimize via Information-Directed Sampling NeurIPS 2014 LIBOL: A Library for Online Learning Algorithms JMLR 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 Online and Stochastic Gradient Methods for Non-decomposable Loss Functions NeurIPS 2014 Online combinatorial optimization with stochastic decision sets and adversarial losses NeurIPS 2014 Online Decision-Making in General Combinatorial Spaces NeurIPS 2014 Online Learning with Composite Loss Functions COLT 2014 Online Linear Optimization via Smoothing COLT 2014 Online Non-Parametric Regression COLT 2014 Online Passive-Aggressive Algorithms for Non-Negative Matrix Factorization and Completion AISTATS 2014 Open Problem: Efficient Online Sparse Regression COLT 2014 Open Problem: Online Local Learning COLT 2014 Open Problem: Shifting Experts on Easy Data COLT 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 Pseudo-reward Algorithms for Contextual Bandits with Linear Payoff Functions ACML 2014 Repeated Contextual Auctions with Strategic Buyers NeurIPS 2014 Resourceful Contextual Bandits COLT 2014