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Dimensionality Reduction

707 papers

Papers per year

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Papers

Multi-Label Prediction via Sparse Infinite CCA NIPS 2009
Heavy-Tailed Symmetric Stochastic Neighbor Embedding NIPS 2009
Variational Gaussian-process factor analysis for modeling spatio-temporal data NIPS 2009
Probabilistic Relational PCA NIPS 2009
Toward Provably Correct Feature Selection in Arbitrary Domains NIPS 2009
Manifold Regularization for SIR with Rate Root-n Convergence NIPS 2009
Locality-sensitive binary codes from shift-invariant kernels NIPS 2009
Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Matrices via Convex Optimization NIPS 2009
Semi-supervised Regression using Hessian energy with an application to semi-supervised dimensionality reduction NIPS 2009
Supervised Exponential Family Principal Component Analysis via Convex Optimization NIPS 2008
ICA based on a Smooth Estimation of the Differential Entropy NIPS 2008
Bayesian Exponential Family PCA NIPS 2008
Diffeomorphic Dimensionality Reduction NIPS 2008
Convergence and Rate of Convergence of a Manifold-Based Dimension Reduction Algorithm NIPS 2008
Theory of matching pursuit NIPS 2008
DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification NIPS 2008
Deflation Methods for Sparse PCA NIPS 2008
Covariance Estimation for High Dimensional Data Vectors Using the Sparse Matrix Transform NIPS 2008
Robust Kernel Principal Component Analysis NIPS 2008
Gaussian-process factor analysis for low-dimensional single-trial analysis of neural population activity NIPS 2008
Kernel Measures of Independence for non-iid Data NIPS 2008
Dimensionality Reduction for Data in Multiple Feature Representations NIPS 2008
Spectral Hashing NIPS 2008
Sparse probabilistic projections NIPS 2008
Reducing statistical dependencies in natural signals using radial Gaussianization NIPS 2008