kernel pca

Kernel PCA for Out-of-Distribution Detection NeurIPS 2024 Contrastive Learning Can Find An Optimal Basis For Approximately View-Invariant Functions ICLR 2023 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 Õ(√n) Random Features NeurIPS 2018 A Stable Multi-Scale Kernel for Topological Machine Learning CVPR 2015 Scale Up Nonlinear Component Analysis with Doubly Stochastic Gradients NeurIPS 2015 Asymmetric Sparse Kernel Approximations for Large-scale Visual Search CVPR 2014 Kernel Mean Estimation via Spectral Filtering NeurIPS 2014 Kernel-PCA Analysis of Surface Normals for Shape-from-Shading CVPR 2014 Subspace Embeddings for the Polynomial Kernel NeurIPS 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 NeurIPS 2008 Denoising and Dimension Reduction in Feature Space NeurIPS 2006 Fast Iterative Kernel PCA NeurIPS 2006 Kernel Maximum Entropy Data Transformation and an Enhanced Spectral Clustering Algorithm NeurIPS 2006 Probabilistic Non-linear Principal Component Analysis with Gaussian Process Latent Variable Models JMLR 2005