Research map / Optimization / Distributed and compressed
The Convergence of Sparsified Gradient Methods
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
- Gradient Sparsification for Communication-Efficient Distributed Optimization (NeurIPS 2018 · similarity 0.91)
- Rethinking gradient sparsification as total error minimization (NeurIPS 2021 · similarity 0.90)
- A Linear Speedup Analysis of Distributed Deep Learning with Sparse and Quantized Communication (NeurIPS 2018 · similarity 0.90)
- ATOMO: Communication-efficient Learning via Atomic Sparsification (NeurIPS 2018 · similarity 0.90)
- Sparsified SGD with Memory (NeurIPS 2018 · similarity 0.90)
- MAST: model-agnostic sparsified training (ICLR 2025 · 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.