Large‐scale knowledge distillation with elastic heterogeneous computing resources

Author:

Liu Ji1ORCID,Dong Daxiang1,Wang Xi1,Qin An1,Li Xingjian1,Valduriez Patrick2,Dou Dejing1,Yu Dianhai1

Affiliation:

1. Baidu Inc. Beijing China

2. LIRMM Inria, University of Montpellier, CNRS Montpellier France

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Reference43 articles.

1. VillegasR YangJ ZouY SohnS LinX LeeH.Learning to generate long‐term future via hierarchical prediction. Proceedings of Machine Learning Research; Vol.70 2017:3560‐3569; PMLR.

2. SzegedyC LiuW JiaY et al.Going deeper with convolutions. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR);2015:1‐9; IEEE Computer Society.

3. DevlinJ ChangMW LeeK ToutanovaK.BERT: pre‐training of deep bidirectional transformers for language understanding. Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL‐HLT);2019:4171‐4186.

4. SunY WangS FengS et al.ERNIE 3.0: large‐scale knowledge enhanced pre‐training for language understanding and generation. arXiv preprint arXiv:2107.02137 2021.

5. CaruanaR LouY GehrkeJ KochP SturmM ElhadadN.Intelligible models for healthcare: predicting pneumonia risk and hospital 30‐day readmission. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining;2015:1721‐1730.

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