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ORCIDWei Dai 0003
Person information
- affiliation: Petuum Inc., Pittsburgh, PA, USA
- affiliation (former): Carnegie Mellon University, Pittsburgh, PA, USA
Other persons with the same name
- Wei Dai — disambiguation page
- Wei Dai 0001
![[0000-0002-4781-3485]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0002-4781-3485")
— Imperial College London, Department of Electrical and Electronic Engineering, UK (and 2 more) - Wei Dai 0002 — Agora.io, Inc. (and 1 more)
- Wei Dai 0004 — China University of Mining Technology, School of Information and Electrical Engineering, Xuzhou, China (and 1 more)
- Wei Dai 0005 — Beihang University, School of Reliability and System Engineering, Beijing, China
- Wei Dai 0006 — New York University School of Medicine, NY, USA (and 1 more)
- Wei Dai 0007 — Microsoft Research, Redmond, WA, USA (and 1 more)
- Wei Dai 0008 — University of California, Santa Barbara, USA
- Wei Dai 0009 — Victoria University, Melbourne, Australia
- Wei Dai 0010 — University of California Irvine, Irvine, CA, USA
- Wei Dai 0011 — University of California, San Diego, USA
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2010 – 2019
- 2019
[c20]Wei Dai, Yi Zhou, Nanqing Dong, Hao Zhang, Eric P. Xing:
Toward Understanding the Impact of Staleness in Distributed Machine Learning. ICLR (Poster) 2019- [c19]Nanqing Dong, Min Xu, Xiaodan Liang, Yiliang Jiang, Wei Dai, Eric P. Xing:
Neural Architecture Search for Adversarial Medical Image Segmentation. MICCAI (6) 2019: 828-836 - 2018
- [b1]Wei Dai:
Learning with Staleness. Carnegie Mellon University, USA, 2018 - [j2]Yi Zhou, Yingbin Liang, Yaoliang Yu, Wei Dai, Eric P. Xing:
Distributed Proximal Gradient Algorithm for Partially Asynchronous Computer Clusters. J. Mach. Learn. Res. 19: 19:1-19:32 (2018) - [c18]Zeya Wang, Nanqing Dong, Wei Dai, Sean D. Rosario, Eric P. Xing:
Classification of Breast Cancer Histopathological Images using Convolutional Neural Networks with Hierarchical Loss and Global Pooling. ICIAR 2018: 745-753 - [c17]Wei Dai, Nanqing Dong, Zeya Wang, Xiaodan Liang, Hao Zhang, Eric P. Xing:
SCAN: Structure Correcting Adversarial Network for Organ Segmentation in Chest X-Rays. DLMIA/ML-CDS@MICCAI 2018: 263-273 - [c16]Nanqing Dong, Michael Kampffmeyer, Xiaodan Liang, Zeya Wang, Wei Dai, Eric P. Xing:
Reinforced Auto-Zoom Net: Towards Accurate and Fast Breast Cancer Segmentation in Whole-Slide Images. DLMIA/ML-CDS@MICCAI 2018: 317-325 - [c15]Nanqing Dong, Michael Kampffmeyer, Xiaodan Liang, Zeya Wang, Wei Dai, Eric P. Xing:
Unsupervised Domain Adaptation for Automatic Estimation of Cardiothoracic Ratio. MICCAI (2) 2018: 544-552 - [c14]Shizhen Xu, Hao Zhang, Graham Neubig, Wei Dai, Jin Kyu Kim, Zhijie Deng, Qirong Ho, Guangwen Yang, Eric P. Xing:
Cavs: An Efficient Runtime System for Dynamic Neural Networks. USENIX ATC 2018: 937-950 - [i12]Nanqing Dong, Michael Kampffmeyer, Xiaodan Liang, Zeya Wang, Wei Dai, Eric P. Xing:
Unsupervised Domain Adaptation for Automatic Estimation of Cardiothoracic Ratio. CoRR abs/1807.03434 (2018) - [i11]Nanqing Dong, Michael Kampffmeyer, Xiaodan Liang, Zeya Wang, Wei Dai, Eric P. Xing:
Reinforced Auto-Zoom Net: Towards Accurate and Fast Breast Cancer Segmentation in Whole-slide Images. CoRR abs/1807.11113 (2018) - [i10]Wei Dai, Yi Zhou, Nanqing Dong, Hao Zhang, Eric P. Xing:
Toward Understanding the Impact of Staleness in Distributed Machine Learning. CoRR abs/1810.03264 (2018) - 2017
- [c13]Xiaodan Liang, Lisa Lee, Wei Dai, Eric P. Xing:
Dual Motion GAN for Future-Flow Embedded Video Prediction. ICCV 2017: 1762-1770 - [c12]Ian En-Hsu Yen, Xiangru Huang, Wei Dai, Pradeep Ravikumar, Inderjit S. Dhillon, Eric P. Xing:
PPDsparse: A Parallel Primal-Dual Sparse Method for Extreme Classification. KDD 2017: 545-553 - [c11]Hao Zhang, Zeyu Zheng, Shizhen Xu, Wei Dai, Qirong Ho, Xiaodan Liang, Zhiting Hu, Jinliang Wei, Pengtao Xie, Eric P. Xing:
Poseidon: An Efficient Communication Architecture for Distributed Deep Learning on GPU Clusters. USENIX ATC 2017: 181-193 - [i9]Wei Dai, Joseph Doyle, Xiaodan Liang, Hao Zhang, Nanqing Dong, Yuan Li, Eric P. Xing:
SCAN: Structure Correcting Adversarial Network for Chest X-rays Organ Segmentation. CoRR abs/1703.08770 (2017) - [i8]Hao Zhang, Zeyu Zheng, Shizhen Xu, Wei Dai, Qirong Ho, Xiaodan Liang, Zhiting Hu, Jinliang Wei, Pengtao Xie, Eric P. Xing:
Poseidon: An Efficient Communication Architecture for Distributed Deep Learning on GPU Clusters. CoRR abs/1706.03292 (2017) - [i7]Xiaodan Liang, Lisa Lee, Wei Dai, Eric P. Xing:
Dual Motion GAN for Future-Flow Embedded Video Prediction. CoRR abs/1708.00284 (2017) - [i6]Hao Zhang, Shizhen Xu, Graham Neubig, Wei Dai, Qirong Ho, Guangwen Yang, Eric P. Xing:
Cavs: A Vertex-centric Programming Interface for Dynamic Neural Networks. CoRR abs/1712.04048 (2017) - 2016
- [c10]Yi Zhou, Yaoliang Yu, Wei Dai, Yingbin Liang, Eric P. Xing:
On Convergence of Model Parallel Proximal Gradient Algorithm for Stale Synchronous Parallel System. AISTATS 2016: 713-722 - [c9]Aaron Harlap, Henggang Cui, Wei Dai, Jinliang Wei, Gregory R. Ganger, Phillip B. Gibbons, Garth A. Gibson, Eric P. Xing:
Addressing the straggler problem for iterative convergent parallel ML. SoCC 2016: 98-111 - [c8]Jin Kyu Kim, Qirong Ho, Seunghak Lee, Xun Zheng, Wei Dai, Garth A. Gibson, Eric P. Xing:
STRADS: a distributed framework for scheduled model parallel machine learning. EuroSys 2016: 5:1-5:16 - [c7]Yu-Xiang Wang, Veeranjaneyulu Sadhanala, Wei Dai, Willie Neiswanger, Suvrit Sra, Eric P. Xing:
Parallel and Distributed Block-Coordinate Frank-Wolfe Algorithms. ICML 2016: 1548-1557 - 2015
- [j1]Eric P. Xing, Qirong Ho, Wei Dai, Jin Kyu Kim, Jinliang Wei, Seunghak Lee, Xun Zheng, Pengtao Xie, Abhimanu Kumar, Yaoliang Yu:
Petuum: A New Platform for Distributed Machine Learning on Big Data. IEEE Trans. Big Data 1(2): 49-67 (2015) - [c6]Wei Dai, Abhimanu Kumar, Jinliang Wei, Qirong Ho, Garth A. Gibson, Eric P. Xing:
High-Performance Distributed ML at Scale through Parameter Server Consistency Models. AAAI 2015: 79-87 - [c5]Jinliang Wei, Wei Dai, Aurick Qiao, Qirong Ho, Henggang Cui, Gregory R. Ganger, Phillip B. Gibbons, Garth A. Gibson, Eric P. Xing:
Managed communication and consistency for fast data-parallel iterative analytics. SoCC 2015: 381-394 - [c4]Eric P. Xing, Qirong Ho, Wei Dai, Jin Kyu Kim, Jinliang Wei, Seunghak Lee, Xun Zheng, Pengtao Xie, Abhimanu Kumar, Yaoliang Yu:
Petuum: A New Platform for Distributed Machine Learning on Big Data. KDD 2015: 1335-1344 - [c3]Jinhui Yuan, Fei Gao, Qirong Ho, Wei Dai, Jinliang Wei, Xun Zheng, Eric Poe Xing, Tie-Yan Liu, Wei-Ying Ma:
LightLDA: Big Topic Models on Modest Computer Clusters. WWW 2015: 1351-1361 - [i5]Eric P. Xing, Qirong Ho, Pengtao Xie, Wei Dai:
Strategies and Principles of Distributed Machine Learning on Big Data. CoRR abs/1512.09295 (2015) - 2014
- [c2]Henggang Cui, Alexey Tumanov, Jinliang Wei, Lianghong Xu, Wei Dai, Jesse Haber-Kucharsky, Qirong Ho, Gregory R. Ganger, Phillip B. Gibbons, Garth A. Gibson, Eric P. Xing:
Exploiting iterative-ness for parallel ML computations. SoCC 2014: 5:1-5:14 - [c1]Henggang Cui, James Cipar, Qirong Ho, Jin Kyu Kim, Seunghak Lee, Abhimanu Kumar, Jinliang Wei, Wei Dai, Gregory R. Ganger, Phillip B. Gibbons, Garth A. Gibson, Eric P. Xing:
Exploiting Bounded Staleness to Speed Up Big Data Analytics. USENIX ATC 2014: 37-48 - [i4]Wei Dai, Abhimanu Kumar, Jinliang Wei, Qirong Ho, Garth A. Gibson, Eric P. Xing:
High-Performance Distributed ML at Scale through Parameter Server Consistency Models. CoRR abs/1410.8043 (2014) - [i3]Jinhui Yuan, Fei Gao, Qirong Ho, Wei Dai, Jinliang Wei, Xun Zheng, Eric P. Xing, Tie-Yan Liu, Wei-Ying Ma:
LightLDA: Big Topic Models on Modest Compute Clusters. CoRR abs/1412.1576 (2014) - 2013
- [i2]Wei Dai, Jinliang Wei, Xun Zheng, Jin Kyu Kim, Seunghak Lee, Junming Yin, Qirong Ho, Eric P. Xing:
Petuum: A Framework for Iterative-Convergent Distributed ML. CoRR abs/1312.7651 (2013) - [i1]Jinliang Wei, Wei Dai, Abhimanu Kumar, Xun Zheng, Qirong Ho, Eric P. Xing:
Consistent Bounded-Asynchronous Parameter Servers for Distributed ML. CoRR abs/1312.7869 (2013)
Coauthor Index
aka: Eric Poe Xing
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