gradient method

Learning Bayesian Nash Equilibrium in Auction Games via Approximate Best Response ICML 2025 Convex Relaxations of ReLU Neural Networks Approximate Global Optima in Polynomial Time ICML 2024 Neural Tangent Kernels for Axis-Aligned Tree Ensembles ICML 2024 Online Bilevel Optimization: Regret Analysis of Online Alternating Gradient Methods AISTATS 2024 On Partial Optimal Transport: Revising the Infeasibility of Sinkhorn and Efficient Gradient Methods AAAI 2024 On the Complexity of Finite-Sum Smooth Optimization under the Polyak–Łojasiewicz Condition ICML 2024 Adversarial Noises Are Linearly Separable for (Nearly) Random Neural Networks AISTATS 2023 A Unified Discretization Framework for Differential Equation Approach with Lyapunov Arguments for Convex Optimization NeurIPS 2023 Fundamental Limits of Two-layer Autoencoders, and Achieving Them with Gradient Methods ICML 2023 Local Convergence of Gradient Methods for Min-Max Games: Partial Curvature Generically Suffices NeurIPS 2023 On Unbalanced Optimal Transport: Gradient Methods, Sparsity and Approximation Error JMLR 2023 Polynomial Preconditioning for Gradient Methods ICML 2023 Sparsity-Constrained Optimal Transport ICLR 2023 Beyond Worst-Case Analysis in Stochastic Approximation: Moment Estimation Improves Instance Complexity ICML 2022 Factorization Approach for Low-complexity Matrix Completion Problems: Exponential Number of Spurious Solutions and Failure of Gradient Methods AISTATS 2022 For Learning in Symmetric Teams, Local Optima are Global Nash Equilibria ICML 2022 Local Linear Convergence of Gradient Methods for Subspace Optimization via Strict Complementarity NeurIPS 2022 On Convergence of Lookahead in Smooth Games AISTATS 2022 A Unified Convergence Analysis for Shuffling-Type Gradient Methods JMLR 2021 On Estimation in Latent Variable Models ICML 2021 On the Bias-Variance-Cost Tradeoff of Stochastic Optimization NeurIPS 2021 Towards Gradient-based Bilevel Optimization with Non-convex Followers and Beyond NeurIPS 2021 Decentralized gradient methods: does topology matter? AISTATS 2020 Gradient Method for Continuous Influence Maximization with Budget-Saving Considerations AAAI 2020 Gradient Temporal-Difference Learning with Regularized Corrections ICML 2020