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Embedding Learning

3751 directly classified papers

Papers per year

Papers

Online Metric Learning and Fast Similarity Search NIPS 2008
Diffeomorphic Dimensionality Reduction NIPS 2008
Spectral Hashing NIPS 2008
Kernelized Sorting NIPS 2008
Colored Maximum Variance Unfolding NIPS 2007
Random Projections for Manifold Learning NIPS 2007
Bayesian Co-Training NIPS 2007
Sparse Overcomplete Latent Variable Decomposition of Counts Data NIPS 2007
Learning the structure of manifolds using random projections NIPS 2007
Euclidean Embedding of Co-occurrence Data JMLR 2007
Learning Spectral Clustering, With Application To Speech Separation JMLR 2006
Large Margin Component Analysis NIPS 2006
Recursive Attribute Factoring NIPS 2006
Approximate Correspondences in High Dimensions NIPS 2006
Learning with Hypergraphs: Clustering, Classification, and Embedding NIPS 2006
MLLE: Modified Locally Linear Embedding Using Multiple Weights NIPS 2006
Convergence of Laplacian Eigenmaps NIPS 2006
Learning to Traverse Image Manifolds NIPS 2006
Learning the Kernel with Hyperkernels JMLR 2005
Inner Product Spaces for Bayesian Networks JMLR 2005
Feature Discovery in Non-Metric Pairwise Data JMLR 2004
Think Globally, Fit Locally: Unsupervised Learning of Low Dimensional Manifolds JMLR 2003
Use of the Zero-Norm with Linear Models and Kernel Methods JMLR 2003
Limitations of Learning Via Embeddings in Euclidean Half Spaces JMLR 2002
Kernel Partial Least Squares Regression in Reproducing Kernel Hilbert Space JMLR 2001