Model Compression

Feature-map-level Online Adversarial Knowledge Distillation ICML 2020 Filter Distillation for Network Compression WACV 2020 Finding trainable sparse networks through Neural Tangent Transfer ICML 2020 Forward and Backward Information Retention for Accurate Binary Neural Networks CVPR 2020 FracTrain: Fractionally Squeezing Bit Savings Both Temporally and Spatially for Efficient DNN Training NeurIPS 2020 Fully Nested Neural Network for Adaptive Compression and Quantization IJCAI 2020 Fully Quantized Transformer for Machine Translation EMNLP 2020 Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing NeurIPS 2020 GhostNet: More Features From Cheap Operations CVPR 2020 Glyph: Fast and Accurately Training Deep Neural Networks on Encrypted Data NeurIPS 2020 Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression CVPR 2020 HAWQ-V2: Hessian Aware trace-Weighted Quantization of Neural Networks NeurIPS 2020 Heterogeneous Knowledge Distillation Using Information Flow Modeling CVPR 2020 HRank: Filter Pruning Using High-Rank Feature Map CVPR 2020 HYDRA: Pruning Adversarially Robust Neural Networks NeurIPS 2020 Information-Theoretic Understanding of Population Risk Improvement with Model Compression AAAI 2020 InstaNAS: Instance-Aware Neural Architecture Search AAAI 2020 Iterative Compression of End-to-End ASR Model Using AutoML Interspeech 2020 LadaBERT: Lightweight Adaptation of BERT through Hybrid Model Compression COLING 2020 Layerwise Sparse Coding for Pruned Deep Neural Networks with Extreme Compression Ratio AAAI 2020 Learnable Bernoulli Dropout for Bayesian Deep Learning AISTATS 2020 Light Multi-Segment Activation for Model Compression AAAI 2020 Lipschitz-Certifiable Training with a Tight Outer Bound NeurIPS 2020 Lookahead: A Far-sighted Alternative of Magnitude-based Pruning ICLR 2020 Low-Rank Compression of Neural Nets: Learning the Rank of Each Layer CVPR 2020