model compression

UER: An Open-Source Toolkit for Pre-training Models EMNLP 2019 Unifying Heterogeneous Classifiers With Distillation CVPR 2019 Universal Approximation Property and Equivalence of Stochastic Computing-Based Neural Networks and Binary Neural Networks AAAI 2019 Universally Slimmable Networks and Improved Training Techniques ICCV 2019 Variational Convolutional Neural Network Pruning CVPR 2019 Whether to Pretrain DNN or not?: An Empirical Analysis for Voice Conversion Interspeech 2019 White-to-Black: Efficient Distillation of Black-Box Adversarial Attacks NAACL 2019 Zero-Shot Knowledge Distillation in Deep Networks ICML 2019 Zero-shot Knowledge Transfer via Adversarial Belief Matching NeurIPS 2019 Accelerating Convolutional Networks via Global & Dynamic Filter Pruning IJCAI 2018 Adversarial Distillation of Bayesian Neural Network Posteriors ICML 2018 Analyzing Filters Toward Efficient ConvNet CVPR 2018 Analyzing Knowledge Distillation in Neural Machine Translation EMNLP 2018 An Optimal Control Approach to Deep Learning and Applications to Discrete-Weight Neural Networks ICML 2018 Apprentice: Using Knowledge Distillation Techniques To Improve Low-Precision Network Accuracy ICLR 2018 Approximation Algorithms for Cascading Prediction Models ICML 2018 Attention-Guided Answer Distillation for Machine Reading Comprehension EMNLP 2018 Automatic DNN Node Pruning Using Mixture Distribution-based Group Regularization Interspeech 2018 Bayesian Compression for Natural Language Processing EMNLP 2018 Better and Faster: Knowledge Transfer from Multiple Self-supervised Learning Tasks via Graph Distillation for Video Classification IJCAI 2018 Binarized LSTM Language Model NAACL 2018 BlockDrop: Dynamic Inference Paths in Residual Networks CVPR 2018 Boosting Self-Supervised Learning via Knowledge Transfer CVPR 2018 Born Again Neural Networks ICML 2018 ChannelNets: Compact and Efficient Convolutional Neural Networks via Channel-Wise Convolutions NeurIPS 2018