Research map / Learning theory and algorithms / Clustering
Metric $k$-clustering using only Weak Comparison Oracles
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
- Coresets for Clustering Using Noisy Comparisons and Few Distance Queries (NeurIPS 2026 · similarity 0.90)
- Low-Distortion Clustering with Ordinal and Limited Cardinal Information (AAAI 2024 · similarity 0.89)
- Faster Query Times for Fully Dynamic $k$-Center Clustering with Outliers (NeurIPS 2023 · similarity 0.89)
- Relative Error Fair Clustering in the Weak-Strong Oracle Model (ICML 2025 · similarity 0.89)
- Approximation Scheme for Weighted Metric Clustering via Sherali-Adams (AAAI 2024 · similarity 0.88)
- Improved Guarantees for Fully Dynamic $k$-Center Clustering with Outliers in General Metric Spaces (NeurIPS 2024 · similarity 0.87)
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.
