Dimensionality Reduction

The Power of Asymmetry in Binary Hashing NeurIPS 2013 Top-Down Segmentation of Non-rigid Visual Objects Using Derivative-Based Search on Sparse Manifolds CVPR 2013 Ultrahigh Dimensional Feature Screening via RKHS Embeddings AISTATS 2013 Unsupervised Spectral Learning of Finite State Transducers NeurIPS 2013 A Geometric take on Metric Learning NeurIPS 2012 Algebraic Geometric Comparison of Probability Distributions JMLR 2012 A nonparametric variable clustering model NeurIPS 2012 A Scalable CUR Matrix Decomposition Algorithm: Lower Time Complexity and Tighter Bound NeurIPS 2012 Convex Multi-view Subspace Learning NeurIPS 2012 Distance Preserving Embeddings for General n-Dimensional Manifolds COLT 2012 Factorial LDA: Sparse Multi-Dimensional Text Models NeurIPS 2012 Feature-aware Label Space Dimension Reduction for Multi-label Classification NeurIPS 2012 Gradient-based kernel method for feature extraction and variable selection NeurIPS 2012 Isotropic Hashing NeurIPS 2012 Kernel Hyperalignment NeurIPS 2012 Latent Coincidence Analysis: A Hidden Variable Model for Distance Metric Learning NeurIPS 2012 Learning Manifolds with K-Means and K-Flats NeurIPS 2012 Local and Global Scaling Reduce Hubs in Space JMLR 2012 Locality Preserving Feature Learning AISTATS 2012 Minimax Rates of Estimation for Sparse PCA in High Dimensions AISTATS 2012 Near-optimal Differentially Private Principal Components NeurIPS 2012 Nonparametric Reduced Rank Regression NeurIPS 2012 Online Clustering of Processes AISTATS 2012 On the Sample Complexity of Robust PCA NeurIPS 2012 Perfect Dimensionality Recovery by Variational Bayesian PCA NeurIPS 2012