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Dimensionality Reduction

707 papers

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Papers

Coordinate-descent for learning orthogonal matrices through Givens rotations ICML 2014
Memory Efficient Kernel Approximation ICML 2014
An Information Geometry of Statistical Manifold Learning ICML 2014
Square Deal: Lower Bounds and Improved Relaxations for Tensor Recovery ICML 2014
Elementary Estimators for Sparse Covariance Matrices and other Structured Moments ICML 2014
Randomized Nonlinear Component Analysis ICML 2014
Nonnegative Sparse PCA with Provable Guarantees ICML 2014
Efficient Dimensionality Reduction for High-Dimensional Network Estimation ICML 2014
Simultaneous Rectification and Alignment via Robust Recovery of Low-rank Tensors NIPS 2013
Low-Rank Matrix and Tensor Completion via Adaptive Sampling NIPS 2013
Sign Cauchy Projections and Chi-Square Kernel NIPS 2013
Robust learning of low-dimensional dynamics from large neural ensembles NIPS 2013
Robust Low Rank Kernel Embeddings of Multivariate Distributions NIPS 2013
Faster Ridge Regression via the Subsampled Randomized Hadamard Transform NIPS 2013
Bayesian inference for low rank spatiotemporal neural receptive fields NIPS 2013
Stochastic Optimization of PCA with Capped MSG NIPS 2013
Near-Optimal Entrywise Sampling for Data Matrices NIPS 2013
Memory Limited, Streaming PCA NIPS 2013
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