Research map / Learning theory and algorithms / Clustering
Accelerating Random Kaczmarz Algorithm Based on Clustering Information
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 |
|---|---|---|---|
| Select the furthest cluster first, then sample rows inside it (RKA-Cluster-JL) | RKA-JL · Synthetic clustered data with Gaussian noise 0.1 or 0.2 | convergence | Helped |
| Build blocks with one row from each cluster (RKA-Cluster-Block) | RKA-Block · Synthetic four-cluster data with Gaussian noise 0.1 or 0.2 | convergence | Helped |
| Build blocks with one row from each cluster | RKA-Block · Synthetic four-cluster data | condition number of blocks | Helped |
| Build blocks with one row from each cluster | RKA-Block · Synthetic four-cluster data | spectral norm of blocks | Helped |
Closest papers by meaning
- Fully-Scalable Massively Parallel Algorithm for k-center with Outliers (AAAI 2025 · similarity 0.84)
- Iterative Methods via Locally Evolving Set Process (NeurIPS 2024 · similarity 0.84)
- Nearly Optimal Approximation of Matrix Functions by the Lanczos Method (NeurIPS 2024 · similarity 0.83)
- Direct Acceleration of Stochastic Root-Finding Without Variance Reduction and Regularization (NeurIPS 2026 · similarity 0.83)
- AT-SKM-Net: An Accelerated Trainable Sampling Kaczmarz-Motzkin Framework for Linear Hard-Constraint Feasibility on Dynamic Graphs (NeurIPS 2026 · similarity 0.83)
- Provable Acceleration of Nesterov's Accelerated Gradient for Asymmetric Matrix Factorization and Linear Neural Networks (NeurIPS 2024 · similarity 0.83)
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.