bookmarks (hide)50
publications (hide)25
- (2019)cite arxiv:1908.09791.
- (2019)cite arxiv:1904.05526.
- (2018)cite arxiv:1811.12359Comment: This is a preliminary preprint.
- (2019)cite arxiv:1906.02940.
- Proceedings of the 36th International Conference on Machine Learning , volume 97 of Proceedings of Machine Learning Research, page 573--582. Long Beach, California, USA, PMLR, (09--15 Jun 2019)
- (2017)cite arxiv:1711.08875Comment: Accepted to CVPR 2018 (Oral).
- (2017)cite arxiv:1707.07012.
- (2017)cite arxiv:1709.05804.
- (2016)cite arxiv:1609.08326Comment: 20 pages, 5 figures.
- (2017)cite arxiv:1701.06538.
- (2019)cite arxiv:1905.07870Comment: 12 pages. Accepted by ACL 2019 Code and resource will be available at https://github.com/EagleW/PaperRobot.
- (2019)cite arxiv:1904.00962.
- (2018)cite arxiv:1805.12152.
- (2019)cite arxiv:1905.02249.
- (2016)cite arxiv:1607.02533Comment: 14 pages, 6 figures. Demo available at https://youtu.be/zQ_uMenoBCk.
- (2017)cite arxiv:1712.01887Comment: we find 99.9% of the gradient exchange in distributed SGD is redundant; we reduce the communication bandwidth by two orders of magnitude without losing accuracy.
- (2019)cite arxiv:1902.01046.
- (2019)cite arxiv:1905.02175.
- (2019)cite arxiv:1904.01569Comment: Technical report.
- (2018)cite arxiv:1802.07088.
