Optimization & Theory

Compressing Neural Networks using the Variational Information Bottleneck ICML 2018 Compressing Word Embeddings via Deep Compositional Code Learning ICLR 2018 Computing Higher Order Derivatives of Matrix and Tensor Expressions NeurIPS 2018 CondenseNet: An Efficient DenseNet Using Learned Group Convolutions CVPR 2018 Conditional-Computation-Based Recurrent Neural Networks for Computationally Efficient Acoustic Modelling Interspeech 2018 Constructing Fast Network through Deconstruction of Convolution NeurIPS 2018 Convergence guarantees for a class of non-convex and non-smooth optimization problems ICML 2018 CosFace: Large Margin Cosine Loss for Deep Face Recognition CVPR 2018 CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes CVPR 2018 CytonMT: an Efficient Neural Machine Translation Open-source Toolkit Implemented in C++ EMNLP 2018 Data-Dependent Stability of Stochastic Gradient Descent ICML 2018 Decorrelated Batch Normalization CVPR 2018 Deep Homogeneous Mixture Models: Representation, Separation, and Approximation NeurIPS 2018 Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions ICML 2018 Deep Neural Networks with Box Convolutions NeurIPS 2018 DeepPINK: reproducible feature selection in deep neural networks NeurIPS 2018 Deformation Aware Image Compression CVPR 2018 Densely Connected Networks for Conversational Speech Recognition Interspeech 2018 Detail-Preserving Pooling in Deep Networks CVPR 2018 Deterministic Binary Filters for Convolutional Neural Networks IJCAI 2018 Diachronic degradation of language models: Insights from social media ACL 2018 DiCE: The Infinitely Differentiable Monte Carlo Estimator ICML 2018 Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization NeurIPS 2018 Dissecting Adam: The Sign, Magnitude and Variance of Stochastic Gradients ICML 2018 Divide and Conquer for Full-Resolution Light Field Deblurring CVPR 2018