online optimization

Tight First- and Second-Order Regret Bounds for Adversarial Linear Bandits NeurIPS 2020 ANYTIME MINIBATCH: EXPLOITING STRAGGLERS IN ONLINE DISTRIBUTED OPTIMIZATION ICLR 2019 Consistent Online Optimization: Convex and Submodular AISTATS 2019 Lifelong Optimization with Low Regret AISTATS 2019 Low-Rank Bandit Methods for High-Dimensional Dynamic Pricing NeurIPS 2019 No-regret algorithms for online k-submodular maximization AISTATS 2019 Optimizing in the Dark: Learning an Optimal Solution through a Simple Request Interface AAAI 2019 Reducing the variance in online optimization by transporting past gradients NeurIPS 2019 Compiling Combinatorial Prediction Games ICML 2018 Methods for off-line/on-line optimization under uncertainty IJCAI 2018 Minimizing Adaptive Regret with One Gradient per Iteration IJCAI 2018 Online Variance Reduction for Stochastic Optimization COLT 2018 Projection-Free Online Optimization with Stochastic Gradient: From Convexity to Submodularity ICML 2018 Affine-Invariant Online Optimization and the Low-rank Experts Problem NeurIPS 2017 Efficiency Through Procrastination: Approximately Optimal Algorithm Configuration with Runtime Guarantees IJCAI 2017 Online Optimization of Smoothed Piecewise Constant Functions AISTATS 2017 Online Optimization of Video-Ad Allocation IJCAI 2017 Stochastic and Adversarial Online Learning without Hyperparameters NeurIPS 2017 An Information-Theoretic Analysis of Thompson Sampling JMLR 2016 Designing smoothing functions for improved worst-case competitive ratio in online optimization NeurIPS 2016 Highly-Smooth Zero-th Order Online Optimization COLT 2016 First-order regret bounds for combinatorial semi-bandits COLT 2015 Online Optimization : Competing with Dynamic Comparators AISTATS 2015 The Hedge Algorithm on a Continuum ICML 2015 A second-order bound with excess losses COLT 2014