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Model Compression

1674 directly classified papers

Papers per year

Papers

Partial Weight Adaptation for Robust DNN Inference CVPR 2020
Regularizing Neural Networks via Minimizing Hyperspherical Energy CVPR 2020
Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression CVPR 2020
Eternal Sunshine of the Spotless Net: Selective Forgetting in Deep Networks CVPR 2020
Low-Rank Compression of Neural Nets: Learning the Rank of Each Layer CVPR 2020
Adaptive Loss-Aware Quantization for Multi-Bit Networks CVPR 2020
The Knowledge Within: Methods for Data-Free Model Compression CVPR 2020
Search to Distill: Pearls Are Everywhere but Not the Eyes CVPR 2020
Rotation Consistent Margin Loss for Efficient Low-Bit Face Recognition CVPR 2020
GAN Compression: Efficient Architectures for Interactive Conditional GANs CVPR 2020
Filter Grafting for Deep Neural Networks CVPR 2020
TBT: Targeted Neural Network Attack With Bit Trojan CVPR 2020
Neural Architecture Search for Lightweight Non-Local Networks CVPR 2020
Structured Multi-Hashing for Model Compression CVPR 2020
ZeroQ: A Novel Zero Shot Quantization Framework CVPR 2020
FIREPruning: Learning-based Filter Pruning for Convolutional Neural Network Compression ACML 2020
Fast Sparse ConvNets CVPR 2020
MnasFPN: Learning Latency-Aware Pyramid Architecture for Object Detection on Mobile Devices CVPR 2020
Towards Accurate Low Bit-Width Quantization with Multiple Phase Adaptations AAAI 2020
Light Multi-Segment Activation for Model Compression AAAI 2020
Regional Tree Regularization for Interpretability in Deep Neural Networks AAAI 2020
Towards Certificated Model Robustness Against Weight Perturbations AAAI 2020
Dynamic Network Pruning with Interpretable Layerwise Channel Selection AAAI 2020
Fractional Skipping: Towards Finer-Grained Dynamic CNN Inference AAAI 2020
DARB: A Density-Adaptive Regular-Block Pruning for Deep Neural Networks AAAI 2020