regret bound

Online Isotonic Regression COLT 2016 Online learning in repeated auctions COLT 2016 Online Learning with Feedback Graphs Without the Graphs ICML 2016 Online Learning with Low Rank Experts COLT 2016 Online Learning with Noisy Side Observations AISTATS 2016 Online PCA with Optimal Regret JMLR 2016 Online Pricing with Strategic and Patient Buyers NeurIPS 2016 Online Sparse Linear Regression COLT 2016 Online Stochastic Linear Optimization under One-bit Feedback ICML 2016 Open Problem: Parameter-Free and Scale-Free Online Algorithms COLT 2016 Open Problem: Second order regret bounds based on scaling time COLT 2016 Optimistic Bandit Convex Optimization NeurIPS 2016 Optimization as Estimation with Gaussian Processes in Bandit Settings AISTATS 2016 Phased Exploration with Greedy Exploitation in Stochastic Combinatorial Partial Monitoring Games NeurIPS 2016 Refined Lower Bounds for Adversarial Bandits NeurIPS 2016 Regret Analysis of the Finite-Horizon Gittins Index Strategy for Multi-Armed Bandits COLT 2016 Regret Bounds for Non-decomposable Metrics with Missing Labels NeurIPS 2016 Regret of Queueing Bandits NeurIPS 2016 Reinforcement Learning of POMDPs using Spectral Methods COLT 2016 Revealing Graph Bandits for Maximizing Local Influence AISTATS 2016 Sample Complexity of Automated Mechanism Design NeurIPS 2016 Scalable Adaptive Stochastic Optimization Using Random Projections NeurIPS 2016 The Multi-fidelity Multi-armed Bandit NeurIPS 2016 Time-Varying Gaussian Process Bandit Optimization AISTATS 2016 Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient ICML 2016