Deep Learning

Learning Sensor Multiplexing Design through Back-propagation NeurIPS 2016 Learning shape correspondence with anisotropic convolutional neural networks NeurIPS 2016 Learning Sigmoid Belief Networks via Monte Carlo Expectation Maximization AISTATS 2016 Learning Simple Algorithms from Examples ICML 2016 Learning Sparse High Dimensional Filters: Image Filtering, Dense CRFs and Bilateral Neural Networks CVPR 2016 Learning Structured Inference Neural Networks With Label Relations CVPR 2016 Learning Structured Sparsity in Deep Neural Networks NeurIPS 2016 Learning Temporal Regularity in Video Sequences CVPR 2016 Learning the Number of Neurons in Deep Networks NeurIPS 2016 Learning to Assign Orientations to Feature Points CVPR 2016 Learning to Co-Generate Object Proposals With a Deep Structured Network CVPR 2016 Learning to Communicate with Deep Multi-Agent Reinforcement Learning NeurIPS 2016 Learning to Generate with Memory ICML 2016 Learning to Match Aerial Images With Deep Attentive Architectures CVPR 2016 Learning to Read Chest X-Rays: Recurrent Neural Cascade Model for Automated Image Annotation CVPR 2016 Learning Transferrable Representations for Unsupervised Domain Adaptation NeurIPS 2016 Learning What and Where to Draw NeurIPS 2016 LightRNN: Memory and Computation-Efficient Recurrent Neural Networks NeurIPS 2016 Linear dynamical neural population models through nonlinear embeddings NeurIPS 2016 Local Similarity-Aware Deep Feature Embedding NeurIPS 2016 LocNet: Improving Localization Accuracy for Object Detection CVPR 2016 LOMo: Latent Ordinal Model for Facial Analysis in Videos CVPR 2016 Longitudinal Face Modeling via Temporal Deep Restricted Boltzmann Machines CVPR 2016 Long Short-Term Memory for Speaker Generalization in Supervised Speech Separation Interspeech 2016 Long Short-term Memory Network over Rhetorical Structure Theory for Sentence-level Sentiment Analysis ACML 2016