model compression

Distilling Multiple Domains for Neural Machine Translation EMNLP 2020 Distilling Neural Networks for Greener and Faster Dependency Parsing ACL 2020 Distilling Portable Generative Adversarial Networks for Image Translation AAAI 2020 Divide and Conquer: Leveraging Intermediate Feature Representations for Quantized Training of Neural Networks ICML 2020 DMCP: Differentiable Markov Channel Pruning for Neural Networks CVPR 2020 Dreaming to Distill: Data-Free Knowledge Transfer via DeepInversion CVPR 2020 DropNet: Reducing Neural Network Complexity via Iterative Pruning ICML 2020 Dual Super-Resolution Learning for Semantic Segmentation CVPR 2020 DWM: A Decomposable Winograd Method for Convolution Acceleration AAAI 2020 DynaBERT: Dynamic BERT with Adaptive Width and Depth NeurIPS 2020 Dynamic Convolution: Attention Over Convolution Kernels CVPR 2020 Dynamic Model Pruning with Feedback ICLR 2020 Dynamic Network Pruning with Interpretable Layerwise Channel Selection AAAI 2020 Dynamic Sparse Training: Find Efficient Sparse Network From Scratch With Trainable Masked Layers ICLR 2020 Early Exiting BERT for Efficient Document Ranking EMNLP 2020 Edinburgh’s Submissions to the 2020 Machine Translation Efficiency Task ACL 2020 Efficient and High-Quality Neural Machine Translation with OpenNMT ACL 2020 Efficient Inference For Neural Machine Translation EMNLP 2020 Efficient Meta Lifelong-Learning with Limited Memory EMNLP 2020 Efficient Neural Vision Systems Based on Convolutional Image Acquisition CVPR 2020 Efficient Residual Dense Block Search for Image Super-Resolution AAAI 2020 Efficient Transformer-based Large Scale Language Representations using Hardware-friendly Block Structured Pruning EMNLP 2020 Efficient WaveGlow: An Improved WaveGlow Vocoder with Enhanced Speed Interspeech 2020 End to End Binarized Neural Networks for Text Classification EMNLP 2020 exBERT: Extending Pre-trained Models with Domain-specific Vocabulary Under Constrained Training Resources EMNLP 2020