Model Compression

Overview of the SustaiNLP 2020 Shared Task EMNLP 2020 PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Real-Time Execution on Mobile Devices AAAI 2020 Plug-in, Trainable Gate for Streamlining Arbitrary Neural Networks AAAI 2020 Predicting Detection Filters for Small Footprint Open-Vocabulary Keyword Spotting Interspeech 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 Q-BERT: Hessian Based Ultra Low Precision Quantization of BERT AAAI 2020 Quantized Compressive Sampling of Stochastic Gradients for Efficient Communication in Distributed Deep Learning AAAI 2020 Radial and Directional Posteriors for Bayesian Deep Learning AAAI 2020 Rank and run-time aware compression of NLP Applications EMNLP 2020 Reborn Filters: Pruning Convolutional Neural Networks with Limited Data AAAI 2020 Regional Tree Regularization for Interpretability in Deep Neural Networks AAAI 2020 Residual Sum-Product Networks PGM 2020 Rethinking Differentiable Search for Mixed-Precision Neural Networks CVPR 2020 Reverse-engineering recurrent neural network solutions to a hierarchical inference task for mice NeurIPS 2020 Robust Quantization: One Model to Rule Them All NeurIPS 2020 RTN: Reparameterized Ternary Network AAAI 2020 SCOP: Scientific Control for Reliable Neural Network Pruning NeurIPS 2020 Search Tree Pruning for Progressive Neural Architecture Search (Student Abstract) AAAI 2020 Sparsity-Inducing Binarized Neural Networks AAAI 2020 Spectral Pruning: Compressing Deep Neural Networks via Spectral Analysis and its Generalization Error IJCAI 2020 SqueezeBERT: What can computer vision teach NLP about efficient neural networks? EMNLP 2020 Structured Convolutions for Efficient Neural Network Design NeurIPS 2020 Structured Multi-Hashing for Model Compression CVPR 2020