Optimization & Theory

Learning Explanations from Language Data EMNLP 2018 Learning Globally Optimized Object Detector via Policy Gradient CVPR 2018 Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data NeurIPS 2018 Learning Patch Reconstructability for Accelerating Multi-View Stereo CVPR 2018 Learning Spatial-Temporal Regularized Correlation Filters for Visual Tracking CVPR 2018 Learning Time/Memory-Efficient Deep Architectures With Budgeted Super Networks CVPR 2018 Learning to Optimize Tensor Programs NeurIPS 2018 Learning towards Minimum Hyperspherical Energy NeurIPS 2018 Learning Versatile Filters for Efficient Convolutional Neural Networks NeurIPS 2018 Link and Code: Fast Indexing With Graphs and Compact Regression Codes CVPR 2018 LISA: Explaining Recurrent Neural Network Judgments via Layer-wIse Semantic Accumulation and Example to Pattern Transformation EMNLP 2018 LiteFlowNet: A Lightweight Convolutional Neural Network for Optical Flow Estimation CVPR 2018 Local Identifiability of ℓ_1-minimization Dictionary Learning: a Sufficient and Almost Necessary Condition JMLR 2018 Low-Latency Video Semantic Segmentation CVPR 2018 Low-rank passthrough neural networks ACL 2018 Marian: Cost-effective High-Quality Neural Machine Translation in C++ ACL 2018 Mean-Variance Loss for Deep Age Estimation From a Face CVPR 2018 MegDet: A Large Mini-Batch Object Detector CVPR 2018 Mesh-TensorFlow: Deep Learning for Supercomputers NeurIPS 2018 Meta-Learning and Universality: Deep Representations and Gradient Descent can Approximate any Learning Algorithm ICLR 2018 Modern Neural Networks Generalize on Small Data Sets NeurIPS 2018 Modular Networks: Learning to Decompose Neural Computation NeurIPS 2018 Modulated Convolutional Networks CVPR 2018 MorphNet: Fast & Simple Resource-Constrained Structure Learning of Deep Networks CVPR 2018 Multi-source transformer with combined losses for automatic post editing EMNLP 2018