Continuous Optimization

On The Complexity of First-Order Methods in Stochastic Bilevel Optimization ICML 2024 On the convergence of adaptive first order methods: Proximal gradient and alternating minimization algorithms L4DC 2024 On the Convergence of Projected Alternating Maximization for Equitable and Optimal Transport JMLR 2024 On the Convergence of Projected Bures-Wasserstein Gradient Descent under Euclidean Strong Convexity ICML 2024 On the Error-Propagation of Inexact Hotelling’s Deflation for Principal Component Analysis ICML 2024 On the Implicit Bias of Adam ICML 2024 On the Last-Iterate Convergence of Shuffling Gradient Methods ICML 2024 On the Maximal Local Disparity of Fairness-Aware Classifiers ICML 2024 On the Nyström Approximation for Preconditioning in Kernel Machines AISTATS 2024 On the Power of Small-size Graph Neural Networks for Linear Programming NeurIPS 2024 On the Unstable Convergence Regime of Gradient Descent AAAI 2024 OPEL: Optimal Transport Guided ProcedurE Learning NeurIPS 2024 Operator-Learning-Inspired Modeling of Neural Ordinary Differential Equations AAAI 2024 Optimal Acceleration for Minimax and Fixed-Point Problems is Not Unique ICML 2024 Optimal Algorithms for Stochastic Bilevel Optimization under Relaxed Smoothness Conditions JMLR 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 Differentially Private Model Training with Public Data ICML 2024 Optimal First-Order Algorithms as a Function of Inequalities JMLR 2024 Optimal Kernel Quantile Learning with Random Features ICML 2024 Optimal Rates for Vector-Valued Spectral Regularization Learning Algorithms NeurIPS 2024 Optimal Transport Aggregation for Visual Place Recognition CVPR 2024 Optimal Transport for Measures with Noisy Tree Metric AISTATS 2024 Optimal Transport with Cyclic Symmetry AAAI 2024