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Dimensionality Reduction

707 papers

Papers per year

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Papers

Convex Multi-view Subspace Learning NIPS 2012
Kernel Hyperalignment NIPS 2012
Perfect Dimensionality Recovery by Variational Bayesian PCA NIPS 2012
A Scalable CUR Matrix Decomposition Algorithm: Lower Time Complexity and Tighter Bound NIPS 2012
Symmetric Correspondence Topic Models for Multilingual Text Analysis NIPS 2012
Factorial LDA: Sparse Multi-Dimensional Text Models NIPS 2012
On the Sample Complexity of Robust PCA NIPS 2012
Semi-supervised Eigenvectors for Locally-biased Learning NIPS 2012
Gradient-based kernel method for feature extraction and variable selection NIPS 2012
Isotropic Hashing NIPS 2012
Semiparametric Principal Component Analysis NIPS 2012
Latent Coincidence Analysis: A Hidden Variable Model for Distance Metric Learning NIPS 2012
A nonparametric variable clustering model NIPS 2012
Smooth-projected Neighborhood Pursuit for High-dimensional Nonparanormal Graph Estimation NIPS 2012
Learning Manifolds with K-Means and K-Flats NIPS 2012
Probabilistic Low-Rank Subspace Clustering NIPS 2012
Feature-aware Label Space Dimension Reduction for Multi-label Classification NIPS 2012
Transelliptical Component Analysis NIPS 2012
Projection Retrieval for Classification NIPS 2012
A Geometric take on Metric Learning NIPS 2012
Nonparametric Reduced Rank Regression NIPS 2012
Sparse Additive Matrix Factorization for Robust PCA and Its Generalization ACML 2012
Topographic Analysis of Correlated Components ACML 2012
Sparse Higher-Order Principal Components Analysis AISTATS 2012
Structured Sparse Canonical Correlation Analysis AISTATS 2012