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Dimensionality Reduction

706 directly classified papers

Papers per year

Papers

Information Bottleneck Optimization and Independent Component Extraction with Spiking Neurons NIPS 2006
New Algorithms for Efficient High-Dimensional Nonparametric Classification JMLR 2006
Graph Laplacian Regularization for Large-Scale Semidefinite Programming NIPS 2006
Blind source separation for over-determined delayed mixtures NIPS 2006
Stratification Learning: Detecting Mixed Density and Dimensionality in High Dimensional Point Clouds NIPS 2006
Differential Entropic Clustering of Multivariate Gaussians NIPS 2006
Manifold Denoising NIPS 2006
Randomized PCA Algorithms with Regret Bounds that are Logarithmic in the Dimension NIPS 2006
Sparse Kernel Orthonormalized PLS for feature extraction in large data sets NIPS 2006
Emergence of conjunctive visual features by quadratic independent component analysis NIPS 2006
Denoising and Dimension Reduction in Feature Space NIPS 2006
MLLE: Modified Locally Linear Embedding Using Multiple Weights NIPS 2006
Unsupervised Regression with Applications to Nonlinear System Identification NIPS 2006
Large Margin Component Analysis NIPS 2006
Fast Iterative Kernel PCA NIPS 2006
Nonnegative Sparse PCA NIPS 2006
Convergence of Laplacian Eigenmaps NIPS 2006
In-Network PCA and Anomaly Detection NIPS 2006
Towards a general independent subspace analysis NIPS 2006
Learning to Traverse Image Manifolds NIPS 2006
Doubly Stochastic Normalization for Spectral Clustering NIPS 2006
On the Nystrom Method for Approximating a Gram Matrix for Improved Kernel-Based Learning JMLR 2005
Efficient Feature Selection via Analysis of Relevance and Redundancy JMLR 2004
Blind Separation of Post-nonlinear Mixtures using Linearizing Transformations and Temporal Decorrelation JMLR 2003
Beyond Independent Components: Trees and Clusters JMLR 2003