| 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 |
Eric XingPresident at Mohamed bin Zayed University of AI, Professor of Computer Science, Carnegie Mellon UEmail được xác minh tại cs.cmu.edu
