Research map / Learning theory and algorithms / Matrix and tensor methods
An Exterior Method for Nonnegative Matrix Factorization
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
- Characterizing the Loss Landscape in Non-Negative Matrix Factorization (AAAI 2021 · similarity 0.91)
- Non-negative Matrix Factorization under Heavy Noise (ICML 2016 · similarity 0.89)
- Dropping Symmetry for Fast Symmetric Nonnegative Matrix Factorization (NeurIPS 2018 · similarity 0.89)
- On the Crucial Role of Initialization for Matrix Factorization (ICLR 2025 · similarity 0.87)
- Statistically Optimal $K$-means Clustering via Nonnegative Low-rank Semidefinite Programming (ICLR 2024 · similarity 0.86)
- Provable Acceleration of Nesterov's Accelerated Gradient for Asymmetric Matrix Factorization and Linear Neural Networks (NeurIPS 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.