model compression

Demystifying and Generalizing BinaryConnect NeurIPS 2021 Dense for the Price of Sparse: Improved Performance of Sparsely Initialized Networks via a Subspace Offset ICML 2021 Densely Guided Knowledge Distillation Using Multiple Teacher Assistants ICCV 2021 Designing a Minimal Retrieve-and-Read System for Open-Domain Question Answering NAACL 2021 Direction is what you need: Improving Word Embedding Compression in Large Language Models ACL 2021 Dirichlet Pruning for Convolutional Neural Networks AISTATS 2021 Disfluency Detection with Unlabeled Data and Small BERT Models Interspeech 2021 DISK-CSV: Distilling Interpretable Semantic Knowledge with a Class Semantic Vector EACL 2021 Distance-Aware Quantization ICCV 2021 Distiller: A Systematic Study of Model Distillation Methods in Natural Language Processing EMNLP 2021 Distilling Image Classifiers in Object Detectors NeurIPS 2021 Distilling Knowledge via Knowledge Review CVPR 2021 Distilling Linguistic Context for Language Model Compression EMNLP 2021 Distilling Object Detectors via Decoupled Features CVPR 2021 Distilling Object Detectors with Feature Richness NeurIPS 2021 Distilling Optimal Neural Networks: Rapid Search in Diverse Spaces ICCV 2021 Distribution Adaptive INT8 Quantization for Training CNNs AAAI 2021 Distribution-Aware Adaptive Multi-Bit Quantization CVPR 2021 Diverse Branch Block: Building a Convolution as an Inception-Like Unit CVPR 2021 Diversifying Sample Generation for Accurate Data-Free Quantization CVPR 2021 Does Knowledge Distillation Really Work? NeurIPS 2021 DominoSearch: Find layer-wise fine-grained N:M sparse schemes from dense neural networks NeurIPS 2021 Double-Win Quant: Aggressively Winning Robustness of Quantized Deep Neural Networks via Random Precision Training and Inference ICML 2021 DPFPS: Dynamic and Progressive Filter Pruning for Compressing Convolutional Neural Networks from Scratch AAAI 2021 DPOQ: Dynamic Precision Onion Quantization ACML 2021