Qirong Ho

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Eric XingPresident at Mohamed bin Zayed University of AI, Professor of Computer Science, Carnegie Mellon UVerifisert e-postadresse på cs.cmu.edu
Wei DaiApple; Carnegie Mellon UniversityVerifisert e-postadresse på cs.cmu.edu
Garth Alan GibsonPresident & CEO, Vector Institute; Consulting Professor of Computer Science, Carnegie MellonVerifisert e-postadresse på vectorinstitute.ai
Seunghak LeeResearch Scientist at FacebookVerifisert e-postadresse på cs.cmu.edu
Jinliang WeiGoogle; Carnegie Mellon UniversityVerifisert e-postadresse på alumni.cmu.edu
Pengtao XieAssistant Professor, UC San Diego; Adjunct Faculty, MBZUAIVerifisert e-postadresse på eng.ucsd.edu
Abhimanu KumarCo-Founder @CausalFunnelVerifisert e-postadresse på cs.cmu.edu
Henggang CuiMotionalVerifisert e-postadresse på motional.com
Hao ZhangUC San DiegoVerifisert e-postadresse på ucsd.edu
Phillip GibbonsCarnegie Mellon UniversityVerifisert e-postadresse på cs.cmu.edu
Yaoliang YuUniversity of WaterlooVerifisert e-postadresse på uwaterloo.ca
Zhiting HuAssistant Professor at UC San DiegoVerifisert e-postadresse på ucsd.edu
Willie NeiswangerAssistant Professor of Computer Science, University of Southern CaliforniaVerifisert e-postadresse på cs.stanford.edu
Jacob EisensteinGoogle ResearchVerifisert e-postadresse på google.com
Amr AhmedSenior Staff Research Scientist, Google AIVerifisert e-postadresse på google.com
Alex SmolaBoson AIVerifisert e-postadresse på smola.org
Choon Hui TeoAmazonVerifisert e-postadresse på amazon.com
Le SongGenBio AI, Mohamed bin Zayed University of Artificial IntelligenceVerifisert e-postadresse på mbzuai.ac.ae
Wei-Ying MaTsinghua UniversityVerifisert e-postadresse på air.tsinghua.edu.cn
Ankur P ParikhStaff Research Scientist at Google DeepMindVerifisert e-postadresse på google.com

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Qirong Ho

Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) and Petuum, Inc

Verifisert e-postadresse på petuum.com - Startside


Tittel Sorter etter sitater Sorter etter år Sorter etter tittel	Sitert av Sitert av	År
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	975	2013
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	657	2015
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	439	2017
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	237	2015
Strategies and principles of distributed machine learning on big data EP Xing, Q Ho, P Xie, D Wei Engineering 2 (2), 179-195, 2016	227	2016
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	210	2014
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	206	2021
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	183	2013
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	172	2014
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	171	2015
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	150	2015
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	112	2011
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	111	2016
Evolving cluster mixed-membership blockmodel for time-evolving networks Q Ho, L Song, E Xing Proceedings of the Fourteenth International Conference on Artificial …, 2011	105	2011
Distributed multi-task relationship learning S Liu, SJ Pan, Q Ho Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge …, 2017	90	2017
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	78	2011
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	65	2018
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	64	2015
Multiscale community blockmodel for network exploration Q Ho, A Parikh, L Song, E Xing Proceedings of the Fourteenth International Conference on Artificial …, 2011	54	2011
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	49	2014

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