Research map / Optimization / Nonconvex and smooth optimization
Efficient Projection-free Algorithms for Saddle Point Problems
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use MPCGS instead of SPFW or SVRE | Robust multiclass classification with a nuclear norm ball constraint · rcv1, sector, and news20 | FW-gap versus running time | Helped |
| Use MPSCGS instead of MPCGS | Robust multiclass classification with a nuclear norm ball constraint · rcv1, sector, and news20 | FW-gap versus running time | Helped |
Closest papers by meaning
- Projection-Free Methods for Solving Nonconvex-Concave Saddle Point Problems (NeurIPS 2023 · similarity 0.93)
- Projection-Free Algorithms for Minimax Problems (ICML 2026 · similarity 0.90)
- A Richer Theory of Convex Constrained Optimization with Reduced Projections and Improved Rates (ICML 2017 · similarity 0.89)
- Revisiting Frank-Wolfe for Structured Nonconvex Optimization (NeurIPS 2025 · similarity 0.87)
- Private Algorithms for Stochastic Saddle Points and Variational Inequalities: Beyond Euclidean Geometry (NeurIPS 2024 · similarity 0.86)
- On Linear Convergence in Smooth Convex-Concave Bilinearly-Coupled Saddle-Point Optimization: Lower Bounds and Optimal Algorithms (ICML 2025 · similarity 0.86)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.
