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Dimensionality Reduction

706 directly classified papers

Papers per year

Papers

Heavy-Tailed Symmetric Stochastic Neighbor Embedding NIPS 2009
Variational Gaussian-process factor analysis for modeling spatio-temporal data NIPS 2009
Semi-supervised Regression using Hessian energy with an application to semi-supervised dimensionality reduction NIPS 2009
Toward Provably Correct Feature Selection in Arbitrary Domains NIPS 2009
Compressed Least-Squares Regression NIPS 2009
Manifold Regularization for SIR with Rate Root-n Convergence NIPS 2009
Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Matrices via Convex Optimization NIPS 2009
Probabilistic Relational PCA NIPS 2009
Dimensionality Reduction for Data in Multiple Feature Representations NIPS 2008
DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification NIPS 2008
Bayesian Exponential Family PCA NIPS 2008
Visualizing Data using t-SNE JMLR 2008
On the Equivalence of Linear Dimensionality-Reducing Transformations JMLR 2008
Manifold Learning: The Price of Normalization JMLR 2008
Theory of matching pursuit NIPS 2008
Kernel Measures of Independence for non-iid Data NIPS 2008
Reducing statistical dependencies in natural signals using radial Gaussianization NIPS 2008
One sketch for all: Theory and Application of Conditional Random Sampling NIPS 2008
Localized Sliced Inverse Regression NIPS 2008
Sparse probabilistic projections NIPS 2008
Spectral Hashing NIPS 2008
Gaussian-process factor analysis for low-dimensional single-trial analysis of neural population activity NIPS 2008
Robust Kernel Principal Component Analysis NIPS 2008
Covariance Estimation for High Dimensional Data Vectors Using the Sparse Matrix Transform NIPS 2008
Deflation Methods for Sparse PCA NIPS 2008