← Core Methods
Machine Learning › Core Methods ›

Embedding Learning

3751 directly classified papers

Papers per year

Papers

Learning Kernels with Radiuses of Minimum Enclosing Balls NIPS 2010
Half Transductive Ranking AISTATS 2010
Pose-Sensitive Embedding by Nonlinear NCA Regression NIPS 2010
Sufficient Dimension Reduction via Squared-loss Mutual Information Estimation AISTATS 2010
Deep Coding Network NIPS 2010
Learning Gradients: Predictive Models that Infer Geometry and Statistical Dependence JMLR 2010
CUR from a Sparse Optimization Viewpoint NIPS 2010
(RF)^2 -- Random Forest Random Field NIPS 2010
Large Scale Online Learning of Image Similarity Through Ranking JMLR 2010
Canonical Time Warping for Alignment of Human Behavior NIPS 2009
Speaker Comparison with Inner Product Discriminant Functions NIPS 2009
Learning When Concepts Abound JMLR 2009
Scalable Collaborative Filtering Approaches for Large Recommender Systems JMLR 2009
Nonparametric Latent Feature Models for Link Prediction NIPS 2009
Nonlinear Learning using Local Coordinate Coding NIPS 2009
Learning Label Embeddings for Nearest-Neighbor Multi-class Classification with an Application to Speech Recognition NIPS 2009
Group Sparse Coding NIPS 2009
Learning to Hash with Binary Reconstructive Embeddings NIPS 2009
Linearly constrained Bayesian matrix factorization for blind source separation NIPS 2009
Efficient Match Kernel between Sets of Features for Visual Recognition NIPS 2009
Fast Graph Laplacian Regularized Kernel Learning via Semidefinite–Quadratic–Linear Programming NIPS 2009
Learning from Neighboring Strokes: Combining Appearance and Context for Multi-Domain Sketch Recognition NIPS 2009
Large Margin Taxonomy Embedding for Document Categorization NIPS 2008
Supervised Bipartite Graph Inference NIPS 2008
Using matrices to model symbolic relationship NIPS 2008