Online Algorithms

A Two-Individual Based Evolutionary Algorithm for the Flexible Job Shop Scheduling Problem AAAI 2019 A Unified Approach to Online Matching with Conflict-Aware Constraints AAAI 2019 Bandit Online Learning with Unknown Delays AISTATS 2019 Bandits with Feedback Graphs and Switching Costs NeurIPS 2019 Batched Multi-armed Bandits Problem NeurIPS 2019 Batch-Size Independent Regret Bounds for the Combinatorial Multi-Armed Bandit Problem COLT 2019 Best of many worlds: Robust model selection for online supervised learning AISTATS 2019 Better Algorithms for Stochastic Bandits with Adversarial Corruptions COLT 2019 Beyond Online Balanced Descent: An Optimal Algorithm for Smoothed Online Optimization NeurIPS 2019 Blink: Fast Connectivity Recovery Entirely in the Data Plane NSDI 2019 Blocking Bandits NeurIPS 2019 Cascaded Algorithm-Selection and Hyper-Parameter Optimization with Extreme-Region Upper Confidence Bound Bandit IJCAI 2019 Cascading Linear Submodular Bandits: Accounting for Position Bias and Diversity in Online Learning to Rank UAI 2019 Categorized Bandits NeurIPS 2019 Censored Semi-Bandits: A Framework for Resource Allocation with Censored Feedback NeurIPS 2019 Combinatorial Bandits with Relative Feedback NeurIPS 2019 Combining Online Learning Guarantees COLT 2019 Competing Against Nash Equilibria in Adversarially Changing Zero-Sum Games ICML 2019 Competitive ratio vs regret minimization: achieving the best of both worlds ALT 2019 Connections Between Mirror Descent, Thompson Sampling and the Information Ratio NeurIPS 2019 Consistent Online Optimization: Convex and Submodular AISTATS 2019 Contextual Bandits with Cross-Learning NeurIPS 2019 Correlated bandits or: How to minimize mean-squared error online ICML 2019 Crawling the Community Structure of Multiplex Networks AAAI 2019 Decentralized Cooperative Stochastic Bandits NeurIPS 2019