model compression

Once-for-All: Train One Network and Specialize it for Efficient Deployment ICLR 2020 One-Shot Pruning of Recurrent Neural Networks by Jacobian Spectrum Evaluation ICLR 2020 Online Knowledge Distillation via Collaborative Learning CVPR 2020 Online Knowledge Distillation with Diverse Peers AAAI 2020 On the Discrepancy between the Theoretical Analysis and Practical Implementations of Compressed Communication for Distributed Deep Learning AAAI 2020 On the weak link between importance and prunability of attention heads EMNLP 2020 Operation-Aware Soft Channel Pruning using Differentiable Masks ICML 2020 Optimal Policy for Deployment of Machine Learning Models on Energy-Bounded Systems IJCAI 2020 Overview of the SustaiNLP 2020 Shared Task EMNLP 2020 Partial Weight Adaptation for Robust DNN Inference CVPR 2020 Passport-aware Normalization for Deep Model Protection NeurIPS 2020 Pay Attention to Features, Transfer Learn Faster CNNs ICLR 2020 PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Real-Time Execution on Mobile Devices AAAI 2020 PENNI: Pruned Kernel Sharing for Efficient CNN Inference ICML 2020 P-KDGAN: Progressive Knowledge Distillation with GANs for One-class Novelty Detection IJCAI 2020 Plug-in, Trainable Gate for Streamlining Arbitrary Neural Networks AAAI 2020 Position-based Scaled Gradient for Model Quantization and Pruning NeurIPS 2020 PoWER-BERT: Accelerating BERT Inference via Progressive Word-vector Elimination ICML 2020 Predicting Detection Filters for Small Footprint Open-Vocabulary Keyword Spotting Interspeech 2020 Propose-and-Attend Single Shot Detector WACV 2020 Pruning Filter in Filter NeurIPS 2020 Pruning from Scratch AAAI 2020 Pruning neural networks without any data by iteratively conserving synaptic flow NeurIPS 2020 Pruning Redundant Mappings in Transformer Models via Spectral-Normalized Identity Prior EMNLP 2020 Pushing the Limits of Narrow Precision Inferencing at Cloud Scale with Microsoft Floating Point NeurIPS 2020