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Dimensionality Reduction

706 directly classified papers

Papers per year

Papers

Sparse Additive Matrix Factorization for Robust PCA and Its Generalization ACML 2012
Topographic Analysis of Correlated Components ACML 2012
Toward Understanding Complex Spaces: Graph Laplacians on Manifolds with Singularities and Boundaries COLT 2012
Semi-supervised Eigenvectors for Locally-biased Learning NIPS 2012
Distance Preserving Embeddings for General n-Dimensional Manifolds COLT 2012
A Scalable CUR Matrix Decomposition Algorithm: Lower Time Complexity and Tighter Bound NIPS 2012
Local and Global Scaling Reduce Hubs in Space JMLR 2012
Algebraic Geometric Comparison of Probability Distributions JMLR 2012
Gradient-based kernel method for feature extraction and variable selection NIPS 2012
Isotropic Hashing NIPS 2012
A nonparametric variable clustering model NIPS 2012
Minimax Rates of Estimation for Sparse PCA in High Dimensions AISTATS 2012
Online Clustering of Processes AISTATS 2012
Locality Preserving Feature Learning AISTATS 2012
Structured Sparse Canonical Correlation Analysis AISTATS 2012
Sparse Higher-Order Principal Components Analysis AISTATS 2012
Nonparametric Reduced Rank Regression NIPS 2012
A Geometric take on Metric Learning NIPS 2012
Transelliptical Component Analysis NIPS 2012
Smooth-projected Neighborhood Pursuit for High-dimensional Nonparanormal Graph Estimation NIPS 2012
Feature-aware Label Space Dimension Reduction for Multi-label Classification NIPS 2012
Projection Retrieval for Classification NIPS 2012
Provable ICA with Unknown Gaussian Noise, with Implications for Gaussian Mixtures and Autoencoders NIPS 2012
Probabilistic Low-Rank Subspace Clustering NIPS 2012
Learning Manifolds with K-Means and K-Flats NIPS 2012