Online Algorithms

Welfare Guarantees from Data NeurIPS 2017 ZigZag: A New Approach to Adaptive Online Learning COLT 2017 A Bandit Framework for Strategic Regression NeurIPS 2016 Accelerating Online Convex Optimization via Adaptive Prediction AISTATS 2016 A Closer Look at Adaptive Regret JMLR 2016 Adaptive Algorithms for Online Convex Optimization with Long-term Constraints ICML 2016 Adaptive Concentration Inequalities for Sequential Decision Problems NeurIPS 2016 An efficient algorithm for contextual bandits with knapsacks, and an extension to concave objectives COLT 2016 An Efficient Streaming Algorithm for the Submodular Cover Problem NeurIPS 2016 An Information-Theoretic Analysis of Thompson Sampling JMLR 2016 An Online Convex Optimization Approach to Blackwell's Approachability JMLR 2016 Anytime optimal algorithms in stochastic multi-armed bandits ICML 2016 (Bandit) Convex Optimization with Biased Noisy Gradient Oracles AISTATS 2016 Coin Betting and Parameter-Free Online Learning NeurIPS 2016 Combinatorial Multi-Armed Bandit and Its Extension to Probabilistically Triggered Arms JMLR 2016 Combinatorial Multi-Armed Bandit with General Reward Functions NeurIPS 2016 Combinatorial semi-bandit with known covariance NeurIPS 2016 Contextual semibandits via supervised learning oracles NeurIPS 2016 Data-driven Rank Breaking for Efficient Rank Aggregation JMLR 2016 Delay and Cooperation in Nonstochastic Bandits COLT 2016 Designing smoothing functions for improved worst-case competitive ratio in online optimization NeurIPS 2016 Double Thompson Sampling for Dueling Bandits NeurIPS 2016 Dual Space Gradient Descent for Online Learning NeurIPS 2016 Dueling Bandits: Beyond Condorcet Winners to General Tournament Solutions NeurIPS 2016 EC-Cache: Load-Balanced, Low-Latency Cluster Caching with Online Erasure Coding OSDI 2016