conditional gradient

A Study of First-Order Methods with a Deterministic Relative-Error Gradient Oracle ICML 2024 Stochastic Frank-Wolfe: Unified Analysis and Zoo of Special Cases AISTATS 2024 A Parameter-Free Conditional Gradient Method for Composite Minimization under Hölder Condition JMLR 2023 Approximate Vanishing Ideal Computations at Scale ICLR 2023 Faster Projection-Free Augmented Lagrangian Methods via Weak Proximal Oracle AISTATS 2023 Linearization Algorithms for Fully Composite Optimization COLT 2023 Projection-Free Methods for Solving Nonconvex-Concave Saddle Point Problems NeurIPS 2023 Projection-Free Methods for Stochastic Simple Bilevel Optimization with Convex Lower-level Problem NeurIPS 2023 A Projection-free Algorithm for Constrained Stochastic Multi-level Composition Optimization NeurIPS 2022 Conditional Gradients for the Approximately Vanishing Ideal AISTATS 2022 Faster One-Sample Stochastic Conditional Gradient Method for Composite Convex Minimization AISTATS 2022 Orthogonal Gromov-Wasserstein discrepancy with efficient lower bound UAI 2022 Pairwise Conditional Gradients without Swap Steps and Sparser Kernel Herding ICML 2022 Projection-free Distributed Online Learning with Sublinear Communication Complexity JMLR 2022 Demystifying and Generalizing BinaryConnect NeurIPS 2021 Heavy Ball Momentum for Conditional Gradient NeurIPS 2021 Parameter-free Locally Accelerated Conditional Gradients ICML 2021 Conditional gradient methods for stochastically constrained convex minimization ICML 2020 Conic Descent and its Application to Memory-efficient Optimization over Positive Semidefinite Matrices NeurIPS 2020 Efficient Projection-free Algorithms for Saddle Point Problems NeurIPS 2020 Improved Regret Bounds for Projection-free Bandit Convex Optimization AISTATS 2020 Locally Accelerated Conditional Gradients AISTATS 2020 Revisiting Frank-Wolfe for Polytopes: Strict Complementarity and Sparsity NeurIPS 2020 Self-Concordant Analysis of Frank-Wolfe Algorithms ICML 2020 Stochastic Conditional Gradient Methods: From Convex Minimization to Submodular Maximization JMLR 2020