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Optimization

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Papers

The Galerkin method beats Graph-Based Approaches for Spectral Algorithms AISTATS 2024
Delegating Data Collection in Decentralized Machine Learning AISTATS 2024
Adaptive Batch Sizes for Active Learning: A Probabilistic Numerics Approach AISTATS 2024
Robust Offline Reinforcement Learning with Heavy-Tailed Rewards AISTATS 2024
Structured Transforms Across Spaces with Cost-Regularized Optimal Transport AISTATS 2024
Directional Optimism for Safe Linear Bandits AISTATS 2024
Generalization Bounds of Nonconvex-(Strongly)-Concave Stochastic Minimax Optimization AISTATS 2024
TransFusion: Covariate-Shift Robust Transfer Learning for High-Dimensional Regression AISTATS 2024
Oracle-Efficient Pessimism: Offline Policy Optimization In Contextual Bandits AISTATS 2024
Lower-level Duality Based Reformulation and Majorization Minimization Algorithm for Hyperparameter Optimization AISTATS 2024
Breaking the Heavy-Tailed Noise Barrier in Stochastic Optimization Problems AISTATS 2024
Adaptive Quasi-Newton and Anderson Acceleration Framework with Explicit Global (Accelerated) Convergence Rates AISTATS 2024
BOBA: Byzantine-Robust Federated Learning with Label Skewness AISTATS 2024
Enhancing Hypergradients Estimation: A Study of Preconditioning and Reparameterization AISTATS 2024
Graph Machine Learning through the Lens of Bilevel Optimization AISTATS 2024
Robust Sparse Voting AISTATS 2024
Efficient Low-Dimensional Compression of Overparameterized Models AISTATS 2024
Fairness in Submodular Maximization over a Matroid Constraint AISTATS 2024
Towards Achieving Sub-linear Regret and Hard Constraint Violation in Model-free RL AISTATS 2024
Distributionally Robust Quickest Change Detection using Wasserstein Uncertainty Sets AISTATS 2024
Submodular Minimax Optimization: Finding Effective Sets AISTATS 2024
Orthogonal Gradient Boosting for Simpler Additive Rule Ensembles AISTATS 2024
Robust variance-regularized risk minimization with concomitant scaling AISTATS 2024
Fast and Adversarial Robust Kernelized SDU Learning AISTATS 2024
Learning Sampling Policy to Achieve Fewer Queries for Zeroth-Order Optimization AISTATS 2024