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Embedding Learning

3751 directly classified papers

Papers per year

Papers

Feature-aware Label Space Dimension Reduction for Multi-label Classification NIPS 2012
Sally: A Tool for Embedding Strings in Vector Spaces JMLR 2012
Metric and Kernel Learning Using a Linear Transformation JMLR 2012
Discussion of “Spectral Dimensionality Reduction via Maximum Entropy” AISTATS 2011
Spectral Dimensionality Reduction via Maximum Entropy AISTATS 2011
PiCoDes: Learning a Compact Code for Novel-Category Recognition NIPS 2011
Similarity-based Learning via Data Driven Embeddings NIPS 2011
Improving Bilingual Projections via Sparse Covariance Matrices EMNLP 2011
Learning a Distance Metric from a Network NIPS 2011
Metric Learning with Multiple Kernels NIPS 2011
Directed Graph Embedding: an Algorithm based on Continuous Limits of Laplacian-type Operators NIPS 2011
A Family of Simple Non-Parametric Kernel Learning Algorithms JMLR 2011
Learning Multi-modal Similarity JMLR 2011
Learning to Search Efficiently in High Dimensions NIPS 2011
Multi-View Learning of Word Embeddings via CCA NIPS 2011
Randomized Algorithms for Comparison-based Search NIPS 2011
Dimensionality Reduction Using the Sparse Linear Model NIPS 2011
Theoretical Analysis of Bayesian Matrix Factorization JMLR 2011
Multi-Label Output Codes using Canonical Correlation Analysis AISTATS 2011
Statistical Optimization of Non-Negative Matrix Factorization AISTATS 2011
On the relation between universality, characteristic kernels and RKHS embedding of measures AISTATS 2010
Factorized Orthogonal Latent Spaces AISTATS 2010
Feature Set Embedding for Incomplete Data NIPS 2010
Sphere Embedding: An Application to Part-of-Speech Induction NIPS 2010
Label Embedding Trees for Large Multi-Class Tasks NIPS 2010