Research map / Optimization / Distributed and compressed
Error Compensated Distributed SGD Can Be Accelerated
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
- Communication-Efficient Distributed Blockwise Momentum SGD with Error-Feedback (NeurIPS 2019 · similarity 0.92)
- PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization (NeurIPS 2019 · similarity 0.92)
- EControl: Fast Distributed Optimization with Compression and Error Control (ICLR 2024 · similarity 0.91)
- Accelerated Methods with Compressed Communications for Distributed Optimization Problems Under Data Similarity (AAAI 2025 · similarity 0.90)
- Approximate Gradient Coding for Distributed Learning with Heterogeneous Stragglers (NeurIPS 2025 · similarity 0.89)
- Scalable Distributed Stochastic Optimization via Bidirectional Compression: Beyond Pessimistic Limits (NeurIPS 2026 · similarity 0.89)
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.
