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Dimensionality Reduction

707 papers

Papers per year

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Papers

Localized Sliced Inverse Regression NIPS 2008
One sketch for all: Theory and Application of Conditional Random Sampling NIPS 2008
Manifold Learning: The Price of Normalization JMLR 2008
On the Equivalence of Linear Dimensionality-Reducing Transformations JMLR 2008
Visualizing Data using t-SNE JMLR 2008
An online Hebbian learning rule that performs Independent Component Analysis NIPS 2007
Random Projections for Manifold Learning NIPS 2007
Receptive Fields without Spike-Triggering NIPS 2007
Colored Maximum Variance Unfolding NIPS 2007
People Tracking with the Laplacian Eigenmaps Latent Variable Model NIPS 2007
A Unified Near-Optimal Estimator For Dimension Reduction in $l_\alpha$ ($0<\alpha\leq 2$) Using Stable Random Projections NIPS 2007
Learning the 2-D Topology of Images NIPS 2007
Sparse Overcomplete Latent Variable Decomposition of Counts Data NIPS 2007
Subspace-Based Face Recognition in Analog VLSI NIPS 2007
Locality and low-dimensions in the prediction of natural experience from fMRI NIPS 2007
Learning the structure of manifolds using random projections NIPS 2007
Discriminative K-means for Clustering NIPS 2007
Heterogeneous Component Analysis NIPS 2007
An Analysis of Inference with the Universum NIPS 2007
Iterative Non-linear Dimensionality Reduction with Manifold Sculpting NIPS 2007
Predicting Brain States from fMRI Data: Incremental Functional Principal Component Regression NIPS 2007
Dimensionality Reduction of Multimodal Labeled Data by Local Fisher Discriminant Analysis JMLR 2007
Bilinear Discriminant Component Analysis JMLR 2007
Graph Laplacians and their Convergence on Random Neighborhood Graphs JMLR 2007
Euclidean Embedding of Co-occurrence Data JMLR 2007