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Minjie Wang
Minjie Wang
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Cited by
Cited by
Year
Mxnet: A flexible and efficient machine learning library for heterogeneous distributed systems
T Chen, M Li, Y Li, M Lin, N Wang, M Wang, T Xiao, B Xu, C Zhang, ...
arXiv preprint arXiv:1512.01274, 2015
24542015
Deep graph library: A graph-centric, highly-performant package for graph neural networks
M Wang, D Zheng, Z Ye, Q Gan, M Li, X Song, J Zhou, C Ma, L Yu, Y Gai, ...
arXiv preprint arXiv:1909.01315, 2019
6632019
Deep graph library: Towards efficient and scalable deep learning on graphs
MY Wang
ICLR workshop on representation learning on graphs and manifolds, 2019
5262019
Supporting very large models using automatic dataflow graph partitioning
M Wang, C Huang, J Li
Proceedings of the Fourteenth EuroSys Conference 2019, 1-17, 2019
1102019
Distdgl: distributed graph neural network training for billion-scale graphs
D Zheng, C Ma, M Wang, J Zhou, Q Su, X Song, Q Gan, Z Zhang, ...
2020 IEEE/ACM 10th Workshop on Irregular Applications: Architectures and …, 2020
702020
Qidong Su, Xiang Song, Quan Gan, Zheng Zhang, and George Karypis. 2020. DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphs
CM Da Zheng, M Wang, J Zhou
arXiv preprint arXiv:2010.05337, 2020
642020
Featgraph: A flexible and efficient backend for graph neural network systems
Y Hu, Z Ye, M Wang, J Yu, D Zheng, M Li, Z Zhang, Z Zhang, Y Wang
SC20: International Conference for High Performance Computing, Networking …, 2020
482020
Mxnet: A flexible and efficient machine learning library for heterogeneous distributed systems. arXiv 2015
T Chen, M Li, Y Li, M Lin, N Wang, M Wang, T Xiao, B Xu, C Zhang, ...
arXiv preprint arXiv:1512.01274, 0
35
Minerva: A scalable and highly efficient training platform for deep learning
M Wang, T Xiao, J Li, J Zhang, C Hong, Z Zhang
NIPS Workshop, Distributed Machine Learning and Matrix Computations, 51, 2014
312014
Deep graph library: towards efficient and scalable deep learning on graphs. CoRR abs/1909.01315 (2019)
M Wang, L Yu, QG Da Zheng, Y Gai, Z Ye, M Li, J Zhou, Q Huang, C Ma, ...
arXiv preprint arXiv:1909.01315, 2019
252019
Impression store: Compressive sensing-based storage for big data analytics
J Zhang, Y Yan, LJ Chen, M Wang, T Moscibroda, Z Zhang
6th {USENIX} Workshop on Hot Topics in Cloud Computing (HotCloud 14), 2014
252014
Unifying data, model and hybrid parallelism in deep learning via tensor tiling
M Wang, C Huang, J Li
arXiv preprint arXiv:1805.04170, 2018
202018
MRI-based radiomics of rectal cancer: assessment of the local recurrence at the site of anastomosis
F Chen, X Ma, S Li, Z Li, Y Jia, Y Xia, M Wang, F Shen, J Lu
Academic Radiology 28, S87-S94, 2021
162021
Scalable graph neural networks with deep graph library
D Zheng, M Wang, Q Gan, X Song, Z Zhang, G Karypis
Proceedings of the 14th ACM International Conference on Web Search and Data …, 2021
152021
A scalable and topology configurable protocol for distributed parameter synchronization
M Wang, H Zhou, M Guo, Z Zhang
Proceedings of 5th Asia-Pacific Workshop on Systems, 1-7, 2014
122014
Learning graph neural networks with deep graph library
D Zheng, M Wang, Q Gan, Z Zhang, G Karypis
Companion Proceedings of the Web Conference 2020, 305-306, 2020
112020
Roller embossing process for the replication of shark‐skin‐inspired micro‐riblets
C Guo, Q Tian, H Wang, J Sun, L Du, M Wang, D Zhao
Micro & Nano Letters 12 (7), 439-444, 2017
112017
Context-aware HCI service selection
Y Shen, M Wang, X Tang, Y Luo, M Guo
Mobile Information Systems 8 (3), 231-254, 2012
112012
Graphiler: Optimizing Graph Neural Networks with Message Passing Data Flow Graph
Z Xie, M Wang, Z Ye, Z Zhang, R Fan
Proceedings of Machine Learning and Systems 4, 515-528, 2022
92022
Distributed hybrid cpu and gpu training for graph neural networks on billion-scale graphs
D Zheng, X Song, C Yang, D LaSalle, Q Su, M Wang, C Ma, G Karypis
arXiv preprint arXiv:2112.15345, 2021
92021
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