Embedding Learning

Distance Preserving Embeddings for General n-Dimensional Manifolds COLT 2012 Exploiting Unrelated Tasks in Multi-Task Learning AISTATS 2012 Feature-aware Label Space Dimension Reduction for Multi-label Classification NeurIPS 2012 Hamming Distance Metric Learning NeurIPS 2012 Isotropic Hashing NeurIPS 2012 Latent Coincidence Analysis: A Hidden Variable Model for Distance Metric Learning NeurIPS 2012 Learning from Distributions via Support Measure Machines NeurIPS 2012 Learning the Dependency Structure of Latent Factors NeurIPS 2012 Lifted coordinate descent for learning with trace-norm regularization AISTATS 2012 Metric and Kernel Learning Using a Linear Transformation JMLR 2012 Primal-Dual methods for sparse constrained matrix completion AISTATS 2012 Random Feature Maps for Dot Product Kernels AISTATS 2012 Sally: A Tool for Embedding Strings in Vector Spaces JMLR 2012 Semi-supervised Eigenvectors for Locally-biased Learning NeurIPS 2012 Super-Bit Locality-Sensitive Hashing NeurIPS 2012 SVDFeature: A Toolkit for Feature-based Collaborative Filtering JMLR 2012 Topic-Partitioned Multinetwork Embeddings NeurIPS 2012 A Family of Simple Non-Parametric Kernel Learning Algorithms JMLR 2011 Dimensionality Reduction Using the Sparse Linear Model NeurIPS 2011 Directed Graph Embedding: an Algorithm based on Continuous Limits of Laplacian-type Operators NeurIPS 2011 Discussion of “Spectral Dimensionality Reduction via Maximum Entropy” AISTATS 2011 Improving Bilingual Projections via Sparse Covariance Matrices EMNLP 2011 Learning a Distance Metric from a Network NeurIPS 2011 Learning Multi-modal Similarity JMLR 2011 Learning to Search Efficiently in High Dimensions NeurIPS 2011