Stebėti
Qirong Ho
Qirong Ho
Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) and Petuum, Inc
Patvirtintas el. paštas petuum.com - Pagrindinis puslapis
Pavadinimas
Cituota
Cituota
Metai
More effective distributed ml via a stale synchronous parallel parameter server
Q Ho, J Cipar, H Cui, S Lee, JK Kim, PB Gibbons, GA Gibson, G Ganger, ...
Advances in neural information processing systems 26, 2013
9632013
Petuum: A new platform for distributed machine learning on big data
EP Xing, Q Ho, W Dai, JK Kim, J Wei, S Lee, X Zheng, P Xie, A Kumar, ...
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge …, 2015
6532015
Poseidon: An efficient communication architecture for distributed deep learning on {GPU} clusters
H Zhang, Z Zheng, S Xu, W Dai, Q Ho, X Liang, Z Hu, J Wei, P Xie, ...
2017 USENIX Annual Technical Conference (USENIX ATC 17), 181-193, 2017
4352017
Lightlda: Big topic models on modest computer clusters
J Yuan, F Gao, Q Ho, W Dai, J Wei, X Zheng, EP Xing, TY Liu, WY Ma
Proceedings of the 24th International Conference on World Wide Web, 1351-1361, 2015
2412015
Strategies and principles of distributed machine learning on big data
EP Xing, Q Ho, P Xie, D Wei
Engineering 2 (2), 179-195, 2016
2162016
Exploiting bounded staleness to speed up big data analytics
H Cui, J Cipar, Q Ho, JK Kim, S Lee, A Kumar, J Wei, W Dai, GR Ganger, ...
2014 USENIX Annual Technical Conference (USENIX ATC 14), 37-48, 2014
2102014
Solving the straggler problem with bounded staleness
J Cipar, Q Ho, JK Kim, S Lee, GR Ganger, G Gibson, K Keeton, E Xing
14th Workshop on Hot Topics in Operating Systems (HotOS XIV), 2013
1742013
Pollux: Co-adaptive cluster scheduling for goodput-optimized deep learning
A Qiao, SK Choe, SJ Subramanya, W Neiswanger, Q Ho, H Zhang, ...
15th {USENIX} Symposium on Operating Systems Design and Implementation …, 2021
1712021
On model parallelization and scheduling strategies for distributed machine learning
S Lee, JK Kim, X Zheng, Q Ho, GA Gibson, EP Xing
Advances in neural information processing systems 27, 2014
1712014
High-performance distributed ML at scale through parameter server consistency models
W Dai, A Kumar, J Wei, Q Ho, G Gibson, E Xing
Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015
1682015
Managed communication and consistency for fast data-parallel iterative analytics
J Wei, W Dai, A Qiao, Q Ho, H Cui, GR Ganger, PB Gibbons, GA Gibson, ...
Proceedings of the Sixth ACM Symposium on Cloud Computing, 381-394, 2015
1492015
Strads: A distributed framework for scheduled model parallel machine learning
JK Kim, Q Ho, S Lee, X Zheng, W Dai, GA Gibson, EP Xing
Proceedings of the Eleventh European Conference on Computer Systems, 1-16, 2016
1172016
Unified analysis of streaming news
A Ahmed, Q Ho, J Eisenstein, E Xing, AJ Smola, CH Teo
Proceedings of the 20th international conference on World wide web, 267-276, 2011
1142011
Evolving cluster mixed-membership blockmodel for time-evolving networks
Q Ho, L Song, E Xing
Proceedings of the Fourteenth International Conference on Artificial …, 2011
892011
Distributed multi-task relationship learning
S Liu, SJ Pan, Q Ho
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge …, 2017
872017
Online inference for the infinite topic-cluster model: Storylines from streaming text
A Ahmed, Q Ho, CH Teo, J Eisenstein, A Smola, E Xing
Proceedings of the Fourteenth International Conference on Artificial …, 2011
782011
Litz: Elastic framework for {High-Performance} distributed machine learning
A Qiao, A Aghayev, W Yu, H Chen, Q Ho, GA Gibson, EP Xing
2018 USENIX Annual Technical Conference (USENIX ATC 18), 631-644, 2018
662018
Poseidon: A system architecture for efficient gpu-based deep learning on multiple machines
H Zhang, Z Hu, J Wei, P Xie, G Kim, Q Ho, E Xing
arXiv preprint arXiv:1512.06216, 2015
662015
Multiscale community blockmodel for network exploration
Q Ho, A Parikh, L Song, E Xing
Proceedings of the Fourteenth International Conference on Artificial …, 2011
562011
Exploiting iterative-ness for parallel ML computations
H Cui, A Tumanov, J Wei, L Xu, W Dai, J Haber-Kucharsky, Q Ho, ...
Proceedings of the ACM Symposium on Cloud Computing, 1-14, 2014
492014
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Straipsniai 1–20