first-order method

First-Order Softmax Weighted Switching Gradient Method for Distributed Stochastic Minimax Optimization with Stochastic Constraints UAI 2026 Rigorous Asymptotics for First-Order Algorithms Through the Dynamical Cavity Method COLT 2026 An Adaptive Parameter-free and Projection-free Restarting Level Set Method for Constrained Convex Optimization Under the Error Bound Condition JMLR 2025 Boosting Perturbed Gradient Ascent for Last-Iterate Convergence in Games ICLR 2025 Wait-Less Offline Tuning and Re-solving for Online Decision Making ICML 2025 Accelerated Algorithms for Constrained Nonconvex-Nonconcave Min-Max Optimization and Comonotone Inclusion ICML 2024 Algorithms for mean-field variational inference via polyhedral optimization in the Wasserstein space COLT 2024 A Primal-Dual Approach to Solving Variational Inequalities with General Constraints ICLR 2024 Decoupling Learning and Decision-Making: Breaking the O(√T) Barrier in Online Resource Allocation with First-Order Methods ICML 2024 Efficient Continual Finite-Sum Minimization ICLR 2024 Faster Accelerated First-order Methods for Convex Optimization with Strongly Convex Function Constraints NeurIPS 2024 Fast Minimization of Expected Logarithmic Loss via Stochastic Dual Averaging AISTATS 2024 First-Order Methods for Linearly Constrained Bilevel Optimization NeurIPS 2024 Functionally Constrained Algorithm Solves Convex Simple Bilevel Problem NeurIPS 2024 Minimax Excess Risk of First-Order Methods for Statistical Learning with Data-Dependent Oracles AISTATS 2024 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 Optimality of Dilated Entropy and Lower Bounds for Online Learning in Extensive-Form Games NeurIPS 2024 On the Scalability and Memory Efficiency of Semidefinite Programs for Lipschitz Constant Estimation of Neural Networks ICLR 2024 Optimal Algorithms for Online Convex Optimization with Adversarial Constraints NeurIPS 2024 PDHG-Unrolled Learning-to-Optimize Method for Large-Scale Linear Programming ICML 2024 Accelerated Cyclic Coordinate Dual Averaging with Extrapolation for Composite Convex Optimization ICML 2023 Accelerated Infeasibility Detection of Constrained Optimization and Fixed-Point Iterations ICML 2023 Accelerated Riemannian Optimization: Handling Constraints with a Prox to Bound Geometric Penalties COLT 2023 Accelerated Single-Call Methods for Constrained Min-Max Optimization ICLR 2023