Research map / Optimization / Nonconvex and smooth optimization
Nesterov Accelerated Shuffling Gradient Method for Convex Optimization
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.
Closest papers by meaning
- Improved Last-Iterate Convergence of Shuffling Gradient Methods for Nonsmooth Convex Optimization (ICML 2025 · similarity 0.92)
- Shuffling Gradient-Based Methods for Nonconvex-Concave Minimax Optimization (NeurIPS 2024 · similarity 0.90)
- On the Last-Iterate Convergence of Shuffling Gradient Methods (ICML 2024 · similarity 0.90)
- Stochastic Extragradient with Flip-Flop Shuffling & Anchoring: Provable Improvements (NeurIPS 2024 · similarity 0.89)
- Revisiting Convergence: Shuffling Complexity Beyond Lipschitz Smoothness (ICML 2025 · similarity 0.89)
- Nesterov acceleration in benignly non-convex landscapes (ICLR 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.
