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Characterizing Deep Learning Training Workloads on Alibaba-PAI

Oct 14, 2019
Mengdi Wang, Chen Meng, Guoping Long, Chuan Wu, Jun Yang, Wei Lin, Yangqing Jia

* Accepted by IISWC2019 

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ChamNet: Towards Efficient Network Design through Platform-Aware Model Adaptation

Dec 21, 2018
Xiaoliang Dai, Peizhao Zhang, Bichen Wu, Hongxu Yin, Fei Sun, Yanghan Wang, Marat Dukhan, Yunqing Hu, Yiming Wu, Yangqing Jia, Peter Vajda, Matt Uyttendaele, Niraj K. Jha


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FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture Search

Dec 14, 2018
Bichen Wu, Xiaoliang Dai, Peizhao Zhang, Yanghan Wang, Fei Sun, Yiming Wu, Yuandong Tian, Peter Vajda, Yangqing Jia, Kurt Keutzer


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Deep Learning Inference in Facebook Data Centers: Characterization, Performance Optimizations and Hardware Implications

Nov 29, 2018
Jongsoo Park, Maxim Naumov, Protonu Basu, Summer Deng, Aravind Kalaiah, Daya Khudia, James Law, Parth Malani, Andrey Malevich, Satish Nadathur, Juan Pino, Martin Schatz, Alexander Sidorov, Viswanath Sivakumar, Andrew Tulloch, Xiaodong Wang, Yiming Wu, Hector Yuen, Utku Diril, Dmytro Dzhulgakov, Kim Hazelwood, Bill Jia, Yangqing Jia, Lin Qiao, Vijay Rao, Nadav Rotem, Sungjoo Yoo, Mikhail Smelyanskiy


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Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour

Apr 30, 2018
Priya Goyal, Piotr Dollár, Ross Girshick, Pieter Noordhuis, Lukasz Wesolowski, Aapo Kyrola, Andrew Tulloch, Yangqing Jia, Kaiming He

* Tech report (v2: correct typos) 

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High performance ultra-low-precision convolutions on mobile devices

Dec 06, 2017
Andrew Tulloch, Yangqing Jia

* Presented at NIPS 2017, Machine Learning on the Phone and other Consumer Devices workshop 

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TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

Mar 16, 2016
Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Jozefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dan Mane, Rajat Monga, Sherry Moore, Derek Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda Viegas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, Xiaoqiang Zheng

* Version 2 updates only the metadata, to correct the formatting of Mart\'in Abadi's name 

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Combining the Best of Convolutional Layers and Recurrent Layers: A Hybrid Network for Semantic Segmentation

Mar 15, 2016
Zhicheng Yan, Hao Zhang, Yangqing Jia, Thomas Breuel, Yizhou Yu

* 14 pages 

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Going Deeper with Convolutions

Sep 17, 2014
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, Andrew Rabinovich


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Caffe: Convolutional Architecture for Fast Feature Embedding

Jun 20, 2014
Yangqing Jia, Evan Shelhamer, Jeff Donahue, Sergey Karayev, Jonathan Long, Ross Girshick, Sergio Guadarrama, Trevor Darrell

* Tech report for the Caffe software at http://github.com/BVLC/Caffe/ 

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Deep Convolutional Ranking for Multilabel Image Annotation

Apr 14, 2014
Yunchao Gong, Yangqing Jia, Thomas Leung, Alexander Toshev, Sergey Ioffe


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One-Shot Adaptation of Supervised Deep Convolutional Models

Feb 18, 2014
Judy Hoffman, Eric Tzeng, Jeff Donahue, Yangqing Jia, Kate Saenko, Trevor Darrell

* ICLR Workshop 2014 

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DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition

Oct 06, 2013
Jeff Donahue, Yangqing Jia, Oriol Vinyals, Judy Hoffman, Ning Zhang, Eric Tzeng, Trevor Darrell


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Why Size Matters: Feature Coding as Nystrom Sampling

Apr 16, 2013
Oriol Vinyals, Yangqing Jia, Trevor Darrell


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Pooling-Invariant Image Feature Learning

Jan 15, 2013
Yangqing Jia, Oriol Vinyals, Trevor Darrell


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Factorized Multi-Modal Topic Model

Oct 16, 2012
Seppo Virtanen, Yangqing Jia, Arto Klami, Trevor Darrell

* Appears in Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence (UAI2012) 

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