Research map / Learning theory and algorithms / Sample complexity
Refined Complexity of PCA with Outliers
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 |
|---|---|---|---|
| Partition candidate subspaces into algebraic-arrangement cells and solve PCA once per resulting outlier set | PCA with Outliers · PCA with Outliers | running time: n^k -> n^{\mathcal{O}(d^2)} | Helped |
| Use the more efficient of the two subspace representations | Algebraic-arrangement reduction · PCA with Outliers | number of PCA instances: \binom{n}{2}^{ ext{one exponent}} -> \binom{n}{2}^{\min(rd, (d - r)d)} 2^{\mathcal{O}(d)} | Helped |
Closest papers by meaning
- Fixed-Parameter and Approximation Algorithms for PCA with Outliers (ICML 2021 · similarity 0.92)
- Efficient Sparse PCA via Block-Diagonalization (ICLR 2025 · similarity 0.86)
- A Geometric Analysis of PCA (NeurIPS 2025 · similarity 0.86)
- Capturing the denoising effect of PCA via compression ratio (NeurIPS 2024 · similarity 0.86)
- Oja's Algorithm for Streaming Sparse PCA (NeurIPS 2024 · similarity 0.85)
- Fast and Provable Algorithms for Sparse PCA with Improved Sample Complexity (ICML 2025 · similarity 0.85)
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.