Research map / Learning theory and algorithms / Matrix and tensor methods
Generalization Bounds for Semi-supervised Matrix Completion with Distributional Side 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.
Closest papers by meaning
- Mixture Matrix Completion (NeurIPS 2018 · similarity 0.90)
- Dynamic matrix recovery from incomplete observations under an exact low-rank constraint (NeurIPS 2016 · similarity 0.89)
- Recommendations with Sparse Comparison Data: Provably Fast Convergence for Nonconvex Matrix Factorization (ICML 2025 · similarity 0.87)
- Online Matrix Completion: A Collaborative Approach with Hott Items (ICML 2024 · similarity 0.87)
- Generalization Analysis of Deep Non-linear Matrix Completion (ICML 2024 · similarity 0.87)
- Symmetric Matrix Completion with ReLU Sampling (ICML 2024 · similarity 0.86)
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.
