Online Algorithms

Efficient and robust algorithms for adversarial linear contextual bandits COLT 2020 Efficient and Robust High-Dimensional Linear Contextual Bandits IJCAI 2020 Efficient improper learning for online logistic regression COLT 2020 Efficient Online Learning of Optimal Rankings: Dimensionality Reduction via Gradient Descent NeurIPS 2020 Exact Passive-Aggressive Algorithms for Multiclass Classification Using Bandit Feedbacks ACML 2020 Exploiting the Surrogate Gap in Online Multiclass Classification NeurIPS 2020 Exploration by Optimisation in Partial Monitoring COLT 2020 Faster Projection-free Online Learning COLT 2020 Fast Rates for Online Prediction with Abstention COLT 2020 Finite Regret and Cycles with Fixed Step-Size via Alternating Gradient Descent-Ascent COLT 2020 Finite-Time Analysis of Round-Robin Kullback-Leibler Upper Confidence Bounds for Optimal Adaptive Allocation with Multiple Plays and Markovian Rewards NeurIPS 2020 Follow the Perturbed Leader: Optimism and Fast Parallel Algorithms for Smooth Minimax Games NeurIPS 2020 Hypothesis Sketching for Online Kernel Selection in Continuous Kernel Space IJCAI 2020 Improper Learning for Non-Stochastic Control COLT 2020 Improved Algorithms for Online Submodular Maximization via First-order Regret Bounds NeurIPS 2020 Improved Regret Bounds for Projection-free Bandit Convex Optimization AISTATS 2020 Improved Sleeping Bandits with Stochastic Action Sets and Adversarial Rewards ICML 2020 Incentivized Exploration for Multi-Armed Bandits under Reward Drift AAAI 2020 Information Directed Sampling for Linear Partial Monitoring COLT 2020 Laplacian-Regularized Graph Bandits: Algorithms and Theoretical Analysis AISTATS 2020 Learning-Augmented Data Stream Algorithms ICLR 2020 Learning Augmented Energy Minimization via Speed Scaling NeurIPS 2020 Learning to Crawl AAAI 2020 Learning to Play Sequential Games versus Unknown Opponents NeurIPS 2020 Leveraging Predictions in Smoothed Online Convex Optimization via Gradient-based Algorithms NeurIPS 2020