Mathematics & Optimization

Bandit Linear Optimization for Sequential Decision Making and Extensive-Form Games AAAI 2021 Bandit Phase Retrieval NeurIPS 2021 Bandits with Knapsacks beyond the Worst Case NeurIPS 2021 Batched Thompson Sampling NeurIPS 2021 Batch greedy maximization of non-submodular functions: Guarantees and applications to experimental design JMLR 2021 Batch Multi-Fidelity Bayesian Optimization with Deep Auto-Regressive Networks NeurIPS 2021 Batch Reinforcement Learning Through Continuation Method ICLR 2021 Bayesian Latent Factor Model for Higher-order Data ACML 2021 Bayesian Optimistic Optimisation with Exponentially Decaying Regret ICML 2021 Bayesian Optimization with High-Dimensional Outputs NeurIPS 2021 Bayesian Persuasion under Ex Ante and Ex Post Constraints AAAI 2021 Bayesian Quadrature on Riemannian Data Manifolds ICML 2021 Benchmarking Scalable Methods for Streaming Cross Document Entity Coreference ACL 2021 Best Arm Identification in Graphical Bilinear Bandits ICML 2021 Best-case lower bounds in online learning NeurIPS 2021 Best-Effort Synthesis: Doing Your Best Is Not Harder Than Giving Up IJCAI 2021 Best Model Identification: A Rested Bandit Formulation ICML 2021 Best of Both Worlds: Practical and Theoretically Optimal Submodular Maximization in Parallel NeurIPS 2021 Better Algorithms for Individually Fair k-Clustering NeurIPS 2021 Better Bounds on the Adaptivity Gap of Influence Maximization under Full-adoption Feedback AAAI 2021 Beyond $log^2(T)$ regret for decentralized bandits in matching markets ICML 2021 Beyond Bandit Feedback in Online Multiclass Classification NeurIPS 2021 Beyond Perturbation Stability: LP Recovery Guarantees for MAP Inference on Noisy Stable Instances AISTATS 2021 Beyond Smoothness: Incorporating Low-Rank Analysis into Nonparametric Density Estimation NeurIPS 2021 Beyond Text: Incorporating Metadata and Label Structure for Multi-Label Document Classification using Heterogeneous Graphs EMNLP 2021