Research map / Learning theory and algorithms / Matrix and tensor methods
Sub-exponential time Sum-of-Squares lower bounds for Principal Components Analysis
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
- Efficient Sparse PCA via Block-Diagonalization (ICLR 2025 · similarity 0.91)
- Upper bounds for Model-Free Row-Sparse Principal Component Analysis (ICML 2020 · similarity 0.91)
- The Complexity of Sparse Tensor PCA (NeurIPS 2021 · similarity 0.90)
- Fast and Provable Algorithms for Sparse PCA with Improved Sample Complexity (ICML 2025 · similarity 0.89)
- Oja's Algorithm for Streaming Sparse PCA (NeurIPS 2024 · similarity 0.88)
- Capturing the denoising effect of PCA via compression ratio (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.
