Model Compression

Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask NeurIPS 2019 Deep Neural Network Quantization via Layer-Wise Optimization Using Limited Training Data AAAI 2019 Deep Virtual Networks for Memory Efficient Inference of Multiple Tasks CVPR 2019 Depthwise Convolution Is All You Need for Learning Multiple Visual Domains AAAI 2019 Dynamic Recursive Neural Network CVPR 2019 ECC: Platform-Independent Energy-Constrained Deep Neural Network Compression via a Bilinear Regression Model CVPR 2019 Efficiency through Auto-Sizing: Notre Dame NLP’s Submission to the WNGT 2019 Efficiency Task EMNLP 2019 Efficient Language Modeling with Automatic Relevance Determination in Recurrent Neural Networks ACL 2019 Efficient Multi-Domain Learning by Covariance Normalization CVPR 2019 Efficient Neural Network Compression CVPR 2019 Efficient Quantization for Neural Networks with Binary Weights and Low Bitwidth Activations AAAI 2019 Efficient Video Classification Using Fewer Frames CVPR 2019 Enhanced Bayesian Compression via Deep Reinforcement Learning CVPR 2019 Exploiting Kernel Sparsity and Entropy for Interpretable CNN Compression CVPR 2019 Filter Pruning via Geometric Median for Deep Convolutional Neural Networks Acceleration CVPR 2019 Focused Quantization for Sparse CNNs NeurIPS 2019 From Research to Production and Back: Ludicrously Fast Neural Machine Translation EMNLP 2019 Fully Learnable Group Convolution for Acceleration of Deep Neural Networks CVPR 2019 Fully Quantized Network for Object Detection CVPR 2019 Gate Decorator: Global Filter Pruning Method for Accelerating Deep Convolutional Neural Networks NeurIPS 2019 Global Sparse Momentum SGD for Pruning Very Deep Neural Networks NeurIPS 2019 Guided Dropout AAAI 2019 HAQ: Hardware-Aware Automated Quantization With Mixed Precision CVPR 2019 HetConv: Heterogeneous Kernel-Based Convolutions for Deep CNNs CVPR 2019 Hybrid 8-bit Floating Point (HFP8) Training and Inference for Deep Neural Networks NeurIPS 2019