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ORCID5th EMC2 2019: Vancouver, Canada
- Fifth Workshop on Energy Efficient Machine Learning and Cognitive Computing - NeurIPS Edition, EMC2@NeurIPS 2019, Vancouver, Canada, December 13, 2019. IEEE 2019, ISBN 978-1-6654-2418-9
- Jingyang Zhang, Huanrui Yang, Fan Chen, Yitu Wang, Hai Li:
Exploring Bit-Slice Sparsity in Deep Neural Networks for Efficient ReRAM-Based Deployment. 1-5 - Jeffrey L. McKinstry, Steven K. Esser, Rathinakumar Appuswamy, Deepika Bablani, John V. Arthur, Izzet B. Yildiz, Dharmendra S. Modha:
Discovering Low-Precision Networks Close to Full-Precision Networks for Efficient Inference. 6-9 - Tianyi Zhang, Zhiqiu Lin, Guandao Yang, Christopher De Sa:
QPyTorch: A Low-Precision Arithmetic Simulation Framework. 10-13 - Yuhui Xu, Yuxi Li, Shuai Zhang, Wei Wen, Botao Wang, Wenrui Dai, Yingyong Qi, Yiran Chen, Weiyao Lin
, Hongkai Xiong:
Trained Rank Pruning for Efficient Deep Neural Networks. 14-17 - Urmish Thakker, Igor Fedorov, Jesse G. Beu, Dibakar Gope, Chu Zhou, Ganesh Dasika, Matthew Mattina:
Pushing the limits of RNN Compression. 18-21 - Alexander Wong, Mahmoud Famouri, Mohammad Javad Shafiee, Francis Li, Brendan Chwyl, Jonathan Chung:
YOLO Nano: a Highly Compact You Only Look Once Convolutional Neural Network for Object Detection. 22-25 - Gonçalo Mordido, Matthijs Van Keirsbilck, Alexander Keller:
Instant Quantization of Neural Networks using Monte Carlo Methods. 26-30 - David Hartmann, Michael Wand:
Progressive Stochastic Binarization of Deep Networks. 31-35 - Ofir Zafrir, Guy Boudoukh, Peter Izsak, Moshe Wasserblat:
Q8BERT: Quantized 8Bit BERT. 36-39 - Shamma Nasrin, Diaa Badawi, Ahmet Enis Çetin, Wilfred Gomes, Amit Ranjan Trivedi:
Towards Co-designing Neural Network Function Approximators with In-SRAM Computing. 40-43 - Peter Izsak, Shira Guskin, Moshe Wasserblat:
Training Compact Models for Low Resource Entity Tagging using Pre-trained Language Models. 44-47 - Qijing Huang, Dequan Wang, Yizhao Gao, Yaohui Cai, Zhen Dong, Bichen Wu, Kurt Keutzer, John Wawrzynek:
Algorithm-hardware Co-design for Deformable Convolution. 48-51 - Prateeth Nayak, David Zhang, Sek Chai:
Bit Efficient Quantization for Deep Neural Networks. 52-56 - Alaa Saade, Joseph Dureau, David Leroy, Francesco Caltagirone, Alice Coucke, Adrien Ball, Clément Doumouro, Thibaut Lavril, Alexandre Caulier, Théodore Bluche, Thibault Gisselbrecht, Maël Primet:
Spoken Language Understanding on the Edge. 57-61 - Tianyu Zhang, Lei Zhu, Qian Zhao, Kilho Shin:
Neural Networks Weights Quantization: Target None-retraining Ternary (TNT). 62-65 - Laura Isabel Galindez Olascoaga, Wannes Meert, Nimish Shah, Guy Van den Broeck, Marian Verhelst:
On Hardware-Aware Probabilistic Frameworks for Resource Constrained Embedded Applications. 66-70
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