Research map / Optimization / Nonconvex and smooth optimization
On Convergence of FedProx: Local Dissimilarity Invariant Bounds, Non-smoothness and Beyond
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
- Stabilized Proximal-Point Methods for Federated Optimization (NeurIPS 2024 · similarity 0.92)
- Methods with Local Steps and Random Reshuffling for Generally Smooth Non-Convex Federated Optimization (ICLR 2025 · similarity 0.90)
- Faster Rates For Federated Variational Inequalities (NeurIPS 2026 · similarity 0.89)
- The Power of Extrapolation in Federated Learning (NeurIPS 2024 · similarity 0.89)
- A New Theoretical Perspective on Data Heterogeneity in Federated Optimization (ICML 2024 · similarity 0.88)
- Federated Optimization with Doubly Regularized Drift Correction (ICML 2024 · similarity 0.88)
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.
