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Model Compression

1674 directly classified papers

Papers per year

Papers

PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Real-Time Execution on Mobile Devices AAAI 2020
AutoCompress: An Automatic DNN Structured Pruning Framework for Ultra-High Compression Rates AAAI 2020
RTN: Reparameterized Ternary Network AAAI 2020
Learning Student Networks with Few Data AAAI 2020
On the Discrepancy between the Theoretical Analysis and Practical Implementations of Compressed Communication for Distributed Deep Learning AAAI 2020
Distilling Portable Generative Adversarial Networks for Image Translation AAAI 2020
AutoDAL: Distributed Active Learning with Automatic Hyperparameter Selection AAAI 2020
Quantized Compressive Sampling of Stochastic Gradients for Efficient Communication in Distributed Deep Learning AAAI 2020
Losing Heads in the Lottery: Pruning Transformer Attention in Neural Machine Translation EMNLP 2020
On the weak link between importance and prunability of attention heads EMNLP 2020
Analyzing Redundancy in Pretrained Transformer Models EMNLP 2020
Vector-Vector-Matrix Architecture: A Novel Hardware-Aware Framework for Low-Latency Inference in NLP Applications EMNLP 2020
Assessment of DistilBERT performance on Named Entity Recognition task for the detection of Protected Health Information and medical concepts EMNLP 2020
Do We Really Need That Many Parameters In Transformer For Extractive Summarization? Discourse Can Help ! EMNLP 2020
Efficient Inference For Neural Machine Translation EMNLP 2020
Early Exiting BERT for Efficient Document Ranking EMNLP 2020
Load What You Need: Smaller Versions of Mutililingual BERT EMNLP 2020
SqueezeBERT: What can computer vision teach NLP about efficient neural networks? EMNLP 2020
FastFormers: Highly Efficient Transformer Models for Natural Language Understanding EMNLP 2020
Binarizing MobileNet via Evolution-Based Searching CVPR 2020
Dynamic Convolution: Attention Over Convolution Kernels CVPR 2020
ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks CVPR 2020
Network Adjustment: Channel Search Guided by FLOPs Utilization Ratio CVPR 2020
Rethinking Depthwise Separable Convolutions: How Intra-Kernel Correlations Lead to Improved MobileNets CVPR 2020
Channel Pruning via Automatic Structure Search IJCAI 2020