Online Learning

User-Specified Local Differential Privacy in Unconstrained Adaptive Online Learning NeurIPS 2019 Acceleration through Optimistic No-Regret Dynamics NeurIPS 2018 Adaptation to Easy Data in Prediction with Limited Advice NeurIPS 2018 Adaptive Exploration-Exploitation Tradeoff for Opportunistic Bandits ICML 2018 Adaptive Learning with Unknown Information Flows NeurIPS 2018 Advancements in Dueling Bandits IJCAI 2018 Bandit Online Learning on Graphs via Adaptive Optimization IJCAI 2018 Compiling Combinatorial Prediction Games ICML 2018 Constant Regret, Generalized Mixability, and Mirror Descent NeurIPS 2018 Contextual bandits with surrogate losses: Margin bounds and efficient algorithms NeurIPS 2018 Contextual Combinatorial Multi-armed Bandits with Volatile Arms and Submodular Reward NeurIPS 2018 Contextual Pricing for Lipschitz Buyers NeurIPS 2018 Cost-aware Cascading Bandits IJCAI 2018 Differential Privacy for Growing Databases NeurIPS 2018 Efficient Online Portfolio with Logarithmic Regret NeurIPS 2018 Factored Bandits NeurIPS 2018 Fast Factorization-free Kernel Learning for Unlabeled Chunk Data Streams IJCAI 2018 Generalized Inverse Optimization through Online Learning NeurIPS 2018 Horizon-Independent Minimax Linear Regression NeurIPS 2018 Improving Online Algorithms via ML Predictions NeurIPS 2018 Infinite-Horizon Gaussian Processes NeurIPS 2018 Learning from discriminative feature feedback NeurIPS 2018 Learning in Games with Lossy Feedback NeurIPS 2018 Learning Optimal Reserve Price against Non-myopic Bidders NeurIPS 2018 Linear Stochastic Approximation: How Far Does Constant Step-Size and Iterate Averaging Go? AISTATS 2018