Metric Learning

A Note on Metric Properties for Some Divergence Measures: The Gaussian Case ACML 2012 A Ranking-based KNN Approach for Multi-Label Classification ACML 2012 Co-Regularized Hashing for Multimodal Data NeurIPS 2012 Diffusion Decision Making for Adaptive k-Nearest Neighbor Classification NeurIPS 2012 Distance Metric Learning with Eigenvalue Optimization JMLR 2012 Distance Preserving Embeddings for General n-Dimensional Manifolds COLT 2012 Feature-aware Label Space Dimension Reduction for Multi-label Classification NeurIPS 2012 Finding Exemplars from Pairwise Dissimilarities via Simultaneous Sparse Recovery NeurIPS 2012 Gradient-based kernel method for feature extraction and variable selection 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 Max-Margin Ratio Machine ACML 2012 Metric and Kernel Learning Using a Linear Transformation JMLR 2012 Multi-Stage Classifier Design ACML 2012 Non-linear Metric Learning NeurIPS 2012 One Permutation Hashing NeurIPS 2012 Online Learning in the Embedded Manifold of Low-rank Matrices JMLR 2012 On-line Reinforcement Learning Using Incremental Kernel-Based Stochastic Factorization NeurIPS 2012 On Sparse, Spectral and Other Parameterizations of Binary Probabilistic Models AISTATS 2012 Optimal kernel choice for large-scale two-sample tests NeurIPS 2012 Parametric Local Metric Learning for Nearest Neighbor Classification NeurIPS 2012 Positive Semidefinite Metric Learning Using Boosting-like Algorithms JMLR 2012 Probabilistic n-Choose-k Models for Classification and Ranking NeurIPS 2012