conftrace_
← Core Methods
Machine Learning › Core Methods ›

Metric Learning

2,854 papers

Papers per year

6
21
102
261
222
'05
'10
'15
'20
'25

Papers

Learning to Assign Orientations to Feature Points CVPR 2016
Improved Hamming Distance Search Using Variable Length Substrings CVPR 2016
Universal Correspondence Network NIPS 2016
Learning Distance Metrics for Multi-Label Classification ACML 2016
The Multiscale Laplacian Graph Kernel NIPS 2016
Deep Metric Learning via Lifted Structured Feature Embedding CVPR 2016
Large Margin Discriminant Dimensionality Reduction in Prediction Space NIPS 2016
Person Re-Identification by Multi-Channel Parts-Based CNN With Improved Triplet Loss Function CVPR 2016
A Simple and Provable Algorithm for Sparse Diagonal CCA ICML 2016
Learning a Discriminative Null Space for Person Re-Identification CVPR 2016
Fast Convergence of Online Pairwise Learning Algorithms AISTATS 2016
Learning Deep Representation for Imbalanced Classification CVPR 2016
Unsupervised Feature Selection by Preserving Stochastic Neighbors AISTATS 2016
Learning Deep Embeddings with Histogram Loss NIPS 2016
Harry: A Tool for Measuring String Similarity JMLR 2016
Closed-Form Training of Mahalanobis Distance for Supervised Clustering CVPR 2016
Efficient Large-Scale Similarity Search Using Matrix Factorization CVPR 2016
Representational Similarity Learning with Application to Brain Networks ICML 2016
Efficient Indexing of Billion-Scale Datasets of Deep Descriptors CVPR 2016
Latent Embeddings for Zero-Shot Classification CVPR 2016
Nearly Isometric Embedding by Relaxation NIPS 2016
Mining Discriminative Triplets of Patches for Fine-Grained Classification CVPR 2016
Improved Error Bounds for Tree Representations of Metric Spaces NIPS 2016
Distance Metric Learning for Aspect Phrase Grouping COLING 2016
Fine-Grained Categorization and Dataset Bootstrapping Using Deep Metric Learning With Humans in the Loop CVPR 2016