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Dimensionality Reduction

706 directly classified papers

Papers per year

Papers

Pass-efficient unsupervised feature selection NIPS 2013
Least Informative Dimensions NIPS 2013
Fantope Projection and Selection: A near-optimal convex relaxation of sparse PCA NIPS 2013
Sparse Additive Text Models with Low Rank Background NIPS 2013
The Power of Asymmetry in Binary Hashing NIPS 2013
Generalizing Analytic Shrinkage for Arbitrary Covariance Structures NIPS 2013
Online Robust PCA via Stochastic Optimization NIPS 2013
Online PCA for Contaminated Data NIPS 2013
On the Sample Complexity of Subspace Learning NIPS 2013
Speeding up Permutation Testing in Neuroimaging NIPS 2013
The Fast Convergence of Incremental PCA NIPS 2013
Robust Transfer Principal Component Analysis with Rank Constraints NIPS 2013
Unsupervised Spectral Learning of Finite State Transducers NIPS 2013
Probabilistic Principal Geodesic Analysis NIPS 2013
Blind Signal Separation in the Presence of Gaussian Noise COLT 2013
Efficient Learning of Simplices COLT 2013
Sparse Principal Component Analysis for High Dimensional Multivariate Time Series AISTATS 2013
Ultrahigh Dimensional Feature Screening via RKHS Embeddings AISTATS 2013
Stress Functions for Nonlinear Dimension Reduction, Proximity Analysis, and Graph Drawing JMLR 2013
On the Convergence of Maximum Variance Unfolding JMLR 2013
A Near-Optimal Algorithm for Differentially-Private Principal Components JMLR 2013
Parallel Vector Field Embedding JMLR 2013
Scalable Optimization of Neighbor Embedding for Visualization ICML 2013
Sparse Uncorrelated Linear Discriminant Analysis ICML 2013
Principal Component Analysis on non-Gaussian Dependent Data ICML 2013