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Model Compression

1928 directly classified papers

Papers per year

Papers

Accelerating Neural Machine Translation with Partial Word Embedding Compression AAAI 2021
Winograd Algorithm for AdderNet ICML 2021
Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization IJCNLP 2021
Strategy and Benchmark for Converting Deep Q-Networks to Event-Driven Spiking Neural Networks AAAI 2021
Bit-Mixer: Mixed-Precision Networks With Runtime Bit-Width Selection ICCV 2021
GhostBERT: Generate More Features with Cheap Operations for BERT ACL 2021
Grey-box Extraction of Natural Language Models ICML 2021
HAWQ-V3: Dyadic Neural Network Quantization ICML 2021
Leveraging Sparse Linear Layers for Debuggable Deep Networks ICML 2021
On the Predictability of Pruning Across Scales ICML 2021
Auxiliary Training: Towards Accurate and Robust Models CVPR 2020
Balancing Cost and Benefit with Tied-Multi Transformers ACL 2020
Passport-aware Normalization for Deep Model Protection NIPS 2020
DFQF: Data Free Quantization-aware Fine-tuning ACML 2020
Model Fusion via Optimal Transport NIPS 2020
HYDRA: Pruning Adversarially Robust Neural Networks NIPS 2020
Pruning Filter in Filter NIPS 2020
FracTrain: Fractionally Squeezing Bit Savings Both Temporally and Spatially for Efficient DNN Training NIPS 2020
TinyTL: Reduce Memory, Not Parameters for Efficient On-Device Learning NIPS 2020
Glyph: Fast and Accurately Training Deep Neural Networks on Encrypted Data NIPS 2020
Residual Distillation: Towards Portable Deep Neural Networks without Shortcuts NIPS 2020
Rotated Binary Neural Network NIPS 2020
Pruning neural networks without any data by iteratively conserving synaptic flow NIPS 2020
Bayesian Bits: Unifying Quantization and Pruning NIPS 2020
Robust Quantization: One Model to Rule Them All NIPS 2020