Research map / Learning theory and algorithms / Matrix and tensor methods
Mean-Shift PCA by Knockoff Mean
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 Multivariate Robust Mean Estimation Under Mean-Shift Contamination (ICML 2025 · similarity 0.85)
- Robust Sub-Gaussian Principal Component Analysis and Width-Independent Schatten Packing (NeurIPS 2020 · similarity 0.85)
- Correlated-PCA: Principal Components' Analysis when Data and Noise are Correlated (NeurIPS 2016 · similarity 0.84)
- Capturing the denoising effect of PCA via compression ratio (NeurIPS 2024 · similarity 0.83)
- PCA++: How Uniformity Induces Robustness to Background Noise in Contrastive Learning (NeurIPS 2025 · similarity 0.81)
- Fast and Provable Algorithms for Sparse PCA with Improved Sample Complexity (ICML 2025 · similarity 0.81)
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.