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Model Compression

1928 directly classified papers

Papers per year

Papers

Neuron Merging: Compensating for Pruned Neurons NIPS 2020
Adversarial Nonnegative Matrix Factorization ICML 2020
Fully Nested Neural Network for Adaptive Compression and Quantization IJCAI 2020
Finding trainable sparse networks through Neural Tangent Transfer ICML 2020
Up or Down? Adaptive Rounding for Post-Training Quantization ICML 2020
Low-Rank Compression of Neural Nets: Learning the Rank of Each Layer CVPR 2020
Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression CVPR 2020
Towards Efficient Model Compression via Learned Global Ranking CVPR 2020
Lipschitz-Certifiable Training with a Tight Outer Bound NIPS 2020
Winning the Lottery with Continuous Sparsification NIPS 2020
AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity NIPS 2020
Adversarially Robust Streaming Algorithms via Differential Privacy NIPS 2020
Compressing LSTM Networks with Hierarchical Coarse-Grain Sparsity INTERSPEECH 2020
Analyzing Redundancy in Pretrained Transformer Models EMNLP 2020
AutoCompress: An Automatic DNN Structured Pruning Framework for Ultra-High Compression Rates AAAI 2020
Do OS abstractions make sense on FPGAs? OSDI 2020
Sparsity-Inducing Binarized Neural Networks AAAI 2020
Layerwise Sparse Coding for Pruned Deep Neural Networks with Extreme Compression Ratio AAAI 2020
RTN: Reparameterized Ternary Network AAAI 2020
When BERT Plays the Lottery, All Tickets Are Winning EMNLP 2020
Extreme Model Compression for On-device Natural Language Understanding COLING 2020
LadaBERT: Lightweight Adaptation of BERT through Hybrid Model Compression COLING 2020
Scale down Transformer by Grouping Features for a Lightweight Character-level Language Model COLING 2020
Beyond Network Pruning: a Joint Search-and-Training Approach IJCAI 2020
A "Network Pruning Network'' Approach to Deep Model Compression WACV 2020