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Model Compression

1503 directly classified papers

Papers per year

Papers

Analysis of Resource-efficient Predictive Models for Natural Language Processing EMNLP 2020
FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions CVPR 2020
Overview of the SustaiNLP 2020 Shared Task EMNLP 2020
HW-TSC’s Participation at WMT 2020 Automatic Post Editing Shared Task EMNLP 2020
Leveraging Filter Correlations for Deep Model Compression WACV 2020
Dynamic Network Pruning with Interpretable Layerwise Channel Selection AAAI 2020
Fast Sparse ConvNets CVPR 2020
ZeroQ: A Novel Zero Shot Quantization Framework CVPR 2020
Structured Multi-Hashing for Model Compression CVPR 2020
SqueezeBERT: What can computer vision teach NLP about efficient neural networks? EMNLP 2020
Sparsity-Inducing Binarized Neural Networks AAAI 2020
Hashing Based Answer Selection AAAI 2020
Q-BERT: Hessian Based Ultra Low Precision Quantization of BERT AAAI 2020
Search Tree Pruning for Progressive Neural Architecture Search (Student Abstract) AAAI 2020
Quantized Compressive Sampling of Stochastic Gradients for Efficient Communication in Distributed Deep Learning AAAI 2020
Efficient WaveGlow: An Improved WaveGlow Vocoder with Enhanced Speed INTERSPEECH 2020
VoiceFilter-Lite: Streaming Targeted Voice Separation for On-Device Speech Recognition INTERSPEECH 2020
MatchboxNet: 1D Time-Channel Separable Convolutional Neural Network Architecture for Speech Commands Recognition INTERSPEECH 2020
Towards Certificated Model Robustness Against Weight Perturbations AAAI 2020
Model Watermarking for Image Processing Networks AAAI 2020
Pruning from Scratch AAAI 2020
Few Shot Network Compression via Cross Distillation AAAI 2020
Information-Theoretic Understanding of Population Risk Improvement with Model Compression AAAI 2020
Predicting Detection Filters for Small Footprint Open-Vocabulary Keyword Spotting INTERSPEECH 2020
On the Discrepancy between the Theoretical Analysis and Practical Implementations of Compressed Communication for Distributed Deep Learning AAAI 2020