Model Compression

Extreme Model Compression for On-device Natural Language Understanding COLING 2020 Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation NeurIPS 2020 FastBERT: a Self-distilling BERT with Adaptive Inference Time ACL 2020 Fast Sparse ConvNets CVPR 2020 FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions CVPR 2020 FetchSGD: Communication-Efficient Federated Learning with Sketching ICML 2020 Few Sample Knowledge Distillation for Efficient Network Compression CVPR 2020 Few Shot Network Compression via Cross Distillation AAAI 2020 FIREPruning: Learning-based Filter Pruning for Convolutional Neural Network Compression ACML 2020 Fractional Skipping: Towards Finer-Grained Dynamic CNN Inference AAAI 2020 Good Subnetworks Provably Exist: Pruning via Greedy Forward Selection ICML 2020 Go Wide, Then Narrow: Efficient Training of Deep Thin Networks ICML 2020 Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression CVPR 2020 Harmonious Coexistence of Structured Weight Pruning and Ternarization for Deep Neural Networks AAAI 2020 Hashing Based Answer Selection AAAI 2020 HAT: Hardware-Aware Transformers for Efficient Natural Language Processing ACL 2020 High Performance Depthwise and Pointwise Convolutions on Mobile Devices AAAI 2020 HW-TSC’s Participation at WMT 2020 Automatic Post Editing Shared Task EMNLP 2020 Improved Knowledge Distillation via Teacher Assistant AAAI 2020 Indirect Stochastic Gradient Quantization and Its Application in Distributed Deep Learning AAAI 2020 Information-Theoretic Understanding of Population Risk Improvement with Model Compression AAAI 2020 Knowledge Consistency between Neural Networks and Beyond ICLR 2020 Large Product Key Memory for Pretrained Language Models EMNLP 2020 Layerwise Sparse Coding for Pruned Deep Neural Networks with Extreme Compression Ratio AAAI 2020 Learning Filter Pruning Criteria for Deep Convolutional Neural Networks Acceleration CVPR 2020