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Embedding Learning

3751 directly classified papers

Papers per year

Papers

Proposal Flow CVPR 2016
Collaborative Recurrent Neural Networks for Dynamic Recommender Systems ACML 2016
Binary embeddings with structured hashed projections ICML 2016
Optimal Sparse Linear Encoders and Sparse PCA NIPS 2016
Phoneme Embedding and its Application to Speech Driven Talking Avatar Synthesis INTERSPEECH 2016
Online Collaborative Learning for Open-Vocabulary Visual Classifiers CVPR 2016
Learning Local Image Descriptors With Deep Siamese and Triplet Convolutional Networks by Minimising Global Loss Functions CVPR 2016
Learning Deep Structure-Preserving Image-Text Embeddings CVPR 2016
Learning Deep Representations of Fine-Grained Visual Descriptions CVPR 2016
Speakers In The Wild (SITW): The QUT Speaker Recognition System INTERSPEECH 2016
Non-negative Matrix Factorization for Discrete Data with Hierarchical Side-Information AISTATS 2016
Scalable and Sound Low-Rank Tensor Learning AISTATS 2016
Learning Distance Metrics for Multi-Label Classification ACML 2016
Preference Completion from Partial Rankings NIPS 2016
Matrix Completion has No Spurious Local Minimum NIPS 2016
Quantized Random Projections and Non-Linear Estimation of Cosine Similarity NIPS 2016
Learning Kernels with Random Features NIPS 2016
Training and Evaluating Multimodal Word Embeddings with Large-scale Web Annotated Images NIPS 2016
Matching Networks for One Shot Learning NIPS 2016
Finite Sample Prediction and Recovery Bounds for Ordinal Embedding NIPS 2016
Learning Deep Embeddings with Histogram Loss NIPS 2016
Exponential Family Embeddings NIPS 2016
Variational Inference for Latent Variables and Uncertain Inputs in Gaussian Processes JMLR 2016
Embedding Label Structures for Fine-Grained Feature Representation CVPR 2016
Deep Metric Learning via Lifted Structured Feature Embedding CVPR 2016