Model Compression

Importance Estimation for Neural Network Pruning CVPR 2019 IRLAS: Inverse Reinforcement Learning for Architecture Search CVPR 2019 Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs ACL 2019 Learning Channel-Wise Interactions for Binary Convolutional Neural Networks CVPR 2019 Learning to Quantize Deep Networks by Optimizing Quantization Intervals With Task Loss CVPR 2019 Learning to Sample CVPR 2019 MBS: Macroblock Scaling for CNN Model Reduction CVPR 2019 MetaQuant: Learning to Quantize by Learning to Penetrate Non-differentiable Quantization NeurIPS 2019 Multi-Precision Quantized Neural Networks via Encoding Decomposition of {-1,+1} AAAI 2019 Network Pruning via Transformable Architecture Search NeurIPS 2019 Network Recasting: A Universal Method for Network Architecture Transformation AAAI 2019 Normalization Helps Training of Quantized LSTM NeurIPS 2019 On-device Structured and Context Partitioned Projection Networks ACL 2019 One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers NeurIPS 2019 On Implicit Filter Level Sparsity in Convolutional Neural Networks CVPR 2019 On the Downstream Performance of Compressed Word Embeddings NeurIPS 2019 Overcoming Multi-model Forgetting ICML 2019 Positive-Unlabeled Compression on the Cloud NeurIPS 2019 Post training 4-bit quantization of convolutional networks for rapid-deployment NeurIPS 2019 PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization NeurIPS 2019 Private Model Compression via Knowledge Distillation AAAI 2019 Projection Convolutional Neural Networks for 1-bit CNNs via Discrete Back Propagation AAAI 2019 Protecting Neural Networks with Hierarchical Random Switching: Towards Better Robustness-Accuracy Trade-off for Stochastic Defenses IJCAI 2019 Quantization Networks CVPR 2019 Re2EMA: Regularized and Reinitialized Exponential Moving Average for Target Model Update in Object Tracking AAAI 2019