Deep Learning

Training Neural Networks Without Gradients: A Scalable ADMM Approach ICML 2016 Transferring Emphasis in Speech Translation Using Hard-Attentional Neural Network Models Interspeech 2016 Triphone State-Tying via Deep Canonical Correlation Analysis Interspeech 2016 Trust No One: Low Rank Matrix Factorization Using Hierarchical RANSAC CVPR 2016 Tweet Sarcasm Detection Using Deep Neural Network COLING 2016 Unconstrained Salient Object Detection via Proposal Subset Optimization CVPR 2016 Understanding and Improving Convolutional Neural Networks via Concatenated Rectified Linear Units ICML 2016 Understanding Real World Indoor Scenes With Synthetic Data CVPR 2016 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks NeurIPS 2016 Unitary Evolution Recurrent Neural Networks ICML 2016 Universal Approximation Results for the Temporal Restricted Boltzmann Machine and the Recurrent Temporal Restricted Boltzmann Machine JMLR 2016 Universal Background Sparse Coding and Multilayer Bootstrap Network for Speaker Clustering Interspeech 2016 Universal Correspondence Network NeurIPS 2016 Unrestricted Vocabulary Keyword Spotting Using LSTM-CTC Interspeech 2016 Unsupervised Cross-Dataset Transfer Learning for Person Re-Identification CVPR 2016 Unsupervised Deep Auditory Model Using Stack of Convolutional RBMs for Speech Recognition Interspeech 2016 Unsupervised Domain Adaptation with Residual Transfer Networks NeurIPS 2016 Unsupervised Learning of 3D Structure from Images NeurIPS 2016 Unsupervised Learning of Acoustic Units Using Autoencoders and Kohonen Nets Interspeech 2016 Unsupervised Learning of Discriminative Attributes and Visual Representations CVPR 2016 Unsupervised Learning of Spoken Language with Visual Context NeurIPS 2016 Use of Generalised Nonlinearity in Vector Taylor Series Noise Compensation for Robust Speech Recognition Interspeech 2016 User Classification with Multiple Textual Perspectives COLING 2016 Using Fast Weights to Attend to the Recent Past NeurIPS 2016 Using Self-Contradiction to Learn Confidence Measures in Stereo Vision CVPR 2016