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Embedding Learning

3,753 papers

Papers per year

2
14
58
474
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Papers

Trace Quotient Meets Sparsity: A Method for Learning Low Dimensional Image Representations CVPR 2016
Learning Local Image Descriptors With Deep Siamese and Triplet Convolutional Networks by Minimising Global Loss Functions CVPR 2016
Fast Training of Triplet-Based Deep Binary Embedding Networks CVPR 2016
Recovering the Missing Link: Predicting Class-Attribute Associations for Unsupervised Zero-Shot Learning CVPR 2016
Revisiting Semi-Supervised Learning with Graph Embeddings ICML 2016
Binary embeddings with structured hashed projections ICML 2016
Beyond CCA: Moment Matching for Multi-View Models ICML 2016
Unsupervised Deep Embedding for Clustering Analysis ICML 2016
Supervised and Semi-Supervised Text Categorization using LSTM for Region Embeddings ICML 2016
Nonparametric Canonical Correlation Analysis ICML 2016
Complex Embeddings for Simple Link Prediction ICML 2016
Cross-Graph Learning of Multi-Relational Associations ICML 2016
Geometric Mean Metric Learning ICML 2016
Recycling Randomness with Structure for Sublinear time Kernel Expansions ICML 2016
Discriminative Embeddings of Latent Variable Models for Structured Data ICML 2016
Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations ICML 2016
Phonetic Context Embeddings for DNN-HMM Phone Recognition INTERSPEECH 2016
Novel Front-End Features Based on Neural Graph Embeddings for DNN-HMM and LSTM-CTC Acoustic Modeling INTERSPEECH 2016
Speakers In The Wild (SITW): The QUT Speaker Recognition System INTERSPEECH 2016
Acoustic Word Embeddings for ASR Error Detection INTERSPEECH 2016
Web Data Selection Based on Word Embedding for Low-Resource Speech Recognition INTERSPEECH 2016
Phoneme Embedding and its Application to Speech Driven Talking Avatar Synthesis INTERSPEECH 2016
An Investigation of Recurrent Neural Network Architectures Using Word Embeddings for Phrase Break Prediction INTERSPEECH 2016
Dialogue Session Segmentation by Embedding-Enhanced TextTiling INTERSPEECH 2016
Hybrid Orthogonal Projection and Estimation (HOPE): A New Framework to Learn Neural Networks JMLR 2016