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Keyword

model compression

Description: Model compression is a set of machine-learning techniques that reduce a model’s size or computational demands while seeking to preserve its predictive performance.
Wikidata ID: wiki/Q131164003
OpenAlex ID: keywords/model-compression
Distilling the Knowledge in a Neural Network
2015 · Hinton, Geoffrey, Vinyals, Oriol, et al. · arXiv (Cornell University) · 14,188
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SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size
2016 · Iandola, Forrest N., Han, Song, et al. · arXiv (Cornell University) · 6,198
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DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
2019 · Schmidt, Wilma Johanna, Grangel-González, Irlan, et al. · arXiv (Cornell University) · 4,652
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Knowledge Distillation: A Survey
2021 · Jianping Gou, Baosheng Yu, et al. · International Journal of Computer Vision · 3,881
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Pruning Filters for Efficient ConvNets
2016 · Li, Hao, Kadav, Asim, et al. · arXiv (Cornell University) · 2,931
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FitNets: Hints for Thin Deep Nets
2014 · Romero, Adriana, Ballas, Nicolas, et al. · arXiv (Cornell University) · 2,859
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Learning Efficient Convolutional Networks through Network Slimming
2017 · Zhuang Liu, Jianguo Li, et al. · IEEE International Conference on Computer Vision (ICCV) · 2,753
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Channel Pruning for Accelerating Very Deep Neural Networks
2017 · Yihui He, Xiangyu Zhang, et al. · IEEE International Conference on Computer Vision (ICCV) · 2,641
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Model compression
2006 · Cristian Buciluǎ, Rich Caruana, et al. · ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) · 2,062
EIE
2016 · Song Han, Xingyu Liu, et al. · ACM SIGARCH Computer Architecture News · 1,934
TinyBERT: Distilling BERT for Natural Language Understanding
2020 · Xiaoqi Jiao, Yichun Yin, et al. · 1,778
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Relational Knowledge Distillation
2019 · Wonpyo Park, Dongju Kim, et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 1,768
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Extensions of recurrent neural network language model
2011 · Tomas Mikolov, Stefan Kombrink, et al. · IEEE International Conference on Acoustics Speech and Signal Processing · 1,594
Wider or Deeper: Revisiting the ResNet Model for Visual Recognition
2019 · Zifeng Wu, Chunhua Shen, et al. · Pattern Recognition · 1,588
Convolutional neural networks at constrained time cost
2015 · Kaiming He, Jian Sun · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 1,559
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A Primer in BERTology: What We Know About How BERT Works
2020 · Anna Rogers, Olga Kovaleva, et al. · Transactions of the Association for Computational Linguistics · 1,544
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AMC: AutoML for Model Compression and Acceleration on Mobile Devices
2018 · Yihui He, Ji Lin, et al. · Lecture notes in computer science · 1,399
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A Survey of Quantization Methods for Efficient Neural Network Inference
2022 · Amir Gholami, Sehoon Kim, et al. · Chapman & Hall/CRC eBooks · 1,203
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Parameter-efficient fine-tuning of large-scale pre-trained language models
2023 · Ning Ding, Yujia Qin, et al. · Nature Machine Intelligence · 1,179
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EfficientNetV2: Smaller Models and Faster Training
2021 · Tan, Mingxing, Le, Quoc V. · arXiv (Cornell University) · 1,100
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ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation
2018 · Sachin Mehta, Mohammad Rastegari, et al. · Lecture notes in computer science · 1,026
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Decoupled Knowledge Distillation
2022 · Borui Zhao, Quan Cui, et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 1,025
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VectorNet: Encoding HD Maps and Agent Dynamics From Vectorized Representation
2020 · Jiyang Gao, Chen Sun, et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 1,006
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HAQ: Hardware-Aware Automated Quantization With Mixed Precision
2019 · Kuan Wang, Zhijian Liu, et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 971
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Knowledge Distillation and Student-Teacher Learning for Visual Intelligence: A Review and New Outlooks
2021 · Lin Wang, Kuk-Jin Yoon · IEEE Transactions on Pattern Analysis and Machine Intelligence · 909
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Works count: 23,040
Citation count: 273,000
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