| 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 | 646 | 2015 |
| Very deep convolutional neural networks for raw waveforms W Dai, C Dai, S Qu, J Li, S Das 2017 IEEE international conference on acoustics, speech and signal …, 2017 | 498 | 2017 |
| 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 | 483* | 2017 |
| Dual motion GAN for future-flow embedded video prediction X Liang, L Lee, W Dai, EP Xing proceedings of the IEEE international conference on computer vision, 1744-1752, 2017 | 442 | 2017 |
| SCAN: Structure Correcting Adversarial Network for Organ Segmentation in Chest X-rays W Dai, J Doyle, X Liang, H Zhang, N Dong, Y Li, EP Xing arXiv preprint arXiv:1703.08770, 2017 | 273 | 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 | 239 | 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 | 214 | 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 |
| A comparison of deep learning methods for environmental sound detection J Li, W Dai, F Metze, S Qu, S Das 2017 IEEE International conference on acoustics, speech and signal …, 2017 | 189 | 2017 |
| 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 | 166 | 2015 |
| Ppdsparse: A parallel primal-dual sparse method for extreme classification IEH Yen, X Huang, W Dai, P Ravikumar, I Dhillon, E Xing Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge …, 2017 | 161 | 2017 |
| Addressing the straggler problem for iterative convergent parallel ML A Harlap, H Cui, W Dai, J Wei, GR Ganger, PB Gibbons, GA Gibson, ... Proceedings of the seventh ACM symposium on cloud computing, 98-111, 2016 | 161 | 2016 |
| 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 | 149 | 2015 |
| 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 | 114 | 2016 |
| Unsupervised domain adaptation for automatic estimation of cardiothoracic ratio N Dong, M Kampffmeyer, X Liang, Z Wang, W Dai, E Xing Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 110 | 2018 |
| Online multi-workflow scheduling under uncertain task execution time in IaaS clouds J Liu, J Ren, W Dai, D Zhang, P Zhou, Y Zhang, G Min, N Najjari IEEE Transactions on Cloud Computing 9 (3), 1180-1194, 2019 | 102 | 2019 |
| Toward understanding the impact of staleness in distributed machine learning W Dai, Y Zhou, N Dong, H Zhang, EP Xing arXiv preprint arXiv:1810.03264, 2018 | 88 | 2018 |
| Benchmarking contemporary deep learning hardware and frameworks: A survey of qualitative metrics W Dai, D Berleant 2019 IEEE First International Conference on Cognitive Machine Intelligence …, 2019 | 78 | 2019 |
| Overcoming invasion of privacy in smart home environment with synthetic packet injection K Yoshigoe, W Dai, M Abramson, A Jacobs 2015 TRON Symposium (TRONSHOW), 1-7, 2015 | 65 | 2015 |
| Parallel and distributed block-coordinate frank-wolfe algorithms YX Wang, V Sadhanala, W Dai, W Neiswanger, S Sra, E Xing International Conference on Machine Learning, 1548-1557, 2016 | 61* | 2016 |
Eric XingPresident at Mohamed bin Zayed University of AI, Professor of Computer Science, Carnegie Mellon UVerified email at cs.cmu.edu
