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Expo Workshop
PaddlePaddle-based Deep Learning at Baidu
Dejing Dou · Chenxia Li · Teng Xi · Dingfu Zhou · Tianyi Wu · Xuhong Li · Zhengjie Huang · Guocheng Niu · Ji Liu · Yaqing Wang · Xin Wang · Qianwei Cai

Sun Jul 18 05:00 PM -- 09:00 PM (PDT) @

PaddlePaddle (PArallel Distributed Deep LEarning) is an easy-to-use, efficient, flexible, and scalable deep learning platform, which was originally developed by Baidu scientists and engineers for the purpose of applying deep learning to many products at Baidu such as Computer Vision (CV), NLP, and Speech. PaddlePaddle supports various neural network architectures and optimization algorithms. With PaddlePaddle, it is possible to leverage many CPUs/GPUs and machines to speed up training, achieving high throughput and performance via optimized communication. In this workshop, Baidu scientists and engineers will present a wide range of PaddlePaddle-based research and projects, from CV, NLP, graph learning, federated learning, few shot learning, to quantum computing.

Author Information

Dejing Dou (Baidu)
Chenxia Li
Teng Xi (Department of Computer Vision Technology (VIS), Baidu Inc.)
Dingfu Zhou
Tianyi Wu
Xuhong Li
Zhengjie Huang
Guocheng Niu
Ji Liu (Baidu research)
Yaqing Wang (Baidu Research)

Yaqing Wang is a staff researcher at Baidu Research. Yaqing obtained Ph.D degree in the Department of Computer Science and Engineering (CSE), Hong Kong University of Science and Technology (HKUST), 2019. She is now working on machine learning, especially on few-shot learning, learning to merge texts and knowledge graphs, and drug discovery.

Xin Wang (Baidu Research)
Qianwei Cai (Baidu)

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