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kernel pca

19 papers

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Co-occurring keywords

kernel methods (1097) kernel principal component analysis (30) dimensionality reduction (720) principal component analysis (316) reproducing kernel hilbert space (334) feature space (219) random feature (89) low-rank approximation (323) model selection (456) stochastic optimization (1060)

Papers

Kernel PCA for Out-of-Distribution Detection NIPS 2024
Efficient fair PCA for fair representation learning AISTATS 2023
Extending Kernel PCA through Dualization: Sparsity, Robustness and Fast Algorithms ICML 2023
Kernel Autocovariance Operators of Stationary Processes: Estimation and Convergence JMLR 2022
Statistical Optimality and Computational Efficiency of Nystrom Kernel PCA JMLR 2022
Model-free Nonconvex Matrix Completion: Local Minima Analysis and Applications in Memory-efficient Kernel PCA JMLR 2019
Streaming Kernel PCA with $\tilde{O}(\sqrt{n})$ Random Features NIPS 2018
Scale Up Nonlinear Component Analysis with Doubly Stochastic Gradients NIPS 2015
A Stable Multi-Scale Kernel for Topological Machine Learning CVPR 2015
Kernel Mean Estimation via Spectral Filtering NIPS 2014
Kernel-PCA Analysis of Surface Normals for Shape-from-Shading CVPR 2014
Asymmetric Sparse Kernel Approximations for Large-scale Visual Search CVPR 2014
Subspace Embeddings for the Polynomial Kernel NIPS 2014
A Framework for Shape Analysis via Hilbert Space Embedding ICCV 2013
On Relevant Dimensions in Kernel Feature Spaces JMLR 2008
Theory of matching pursuit NIPS 2008
Denoising and Dimension Reduction in Feature Space NIPS 2006
Fast Iterative Kernel PCA NIPS 2006
Probabilistic Non-linear Principal Component Analysis with Gaussian Process Latent Variable Models JMLR 2005