Mathematics & Optimization

Optimal Algorithms for Stochastic Bilevel Optimization under Relaxed Smoothness Conditions JMLR 2024 Optimal Attack and Defense for Reinforcement Learning AAAI 2024 Optimal Auction Design with User Coupons in Advertising Systems IJCAI 2024 Optimal Batched Linear Bandits ICML 2024 Optimal bounds for ℓ_p sensitivity sampling via ℓ_2 augmentation ICML 2024 Optimal Coresets for Low-Dimensional Geometric Median ICML 2024 Optimal Decision Tree and Adaptive Submodular Ranking with Noisy Outcomes JMLR 2024 Optimal deep learning of holomorphic operators between Banach spaces NeurIPS 2024 Optimal Design for Human Preference Elicitation NeurIPS 2024 Optimal Differentially Private Model Training with Public Data ICML 2024 Optimal estimation of Gaussian (poly)trees AISTATS 2024 Optimal Exploration is no harder than Thompson Sampling AISTATS 2024 Optimal Extended Formulations from Optimal Dynamic Programming Algorithms IJCAI 2024 Optimal First-Order Algorithms as a Function of Inequalities JMLR 2024 Optimal Kernel Quantile Learning with Random Features ICML 2024 Optimal Learning Policies for Differential Privacy in Multi-armed Bandits JMLR 2024 Optimally Improving Cooperative Learning in a Social Setting ICML 2024 Optimal Makespan in a Minute Timespan! A Scalable Multi-Robot Goal Assignment Algorithm for Minimizing Mission Time AAAI 2024 Optimal Mechanism in a Dynamic Stochastic Knapsack Environment AAAI 2024 Optimal Multiclass U-Calibration Error and Beyond NeurIPS 2024 Optimal Multi-Fidelity Best-Arm Identification NeurIPS 2024 Optimal Private and Communication Constraint Distributed Goodness-of-Fit Testing for Discrete Distributions in the Large Sample Regime NeurIPS 2024 Optimal Quasi-clique: Hardness, Equivalence with Densest-k-Subgraph, and Quasi-partitioned Community Mining AAAI 2024 Optimal Rates for Vector-Valued Spectral Regularization Learning Algorithms NeurIPS 2024 Optimal Scalarizations for Sublinear Hypervolume Regret NeurIPS 2024