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ORCIDJiawei Jiang 0001
Person information
- affiliation: Wuhan University, School of Computer Science, China
- affiliation (PhD 2018): Peking University, Beijing, China
Other persons with the same name
- Jiawei Jiang — disambiguation page
- Jiawei Jiang 0002
![[0000-0002-9200-9189]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0002-9200-9189")
— Zhejiang University of Technology, College of Computer Science and Technology, Hangzhou, China - Jiawei Jiang 0003 — Beihang University, School of Computer Science and Engineering, Beijing, China
Other persons with a similar name
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2020 – today
- 2024
[j14]Fangcheng Fu, Xuanyu Wang, Jiawei Jiang, Huanran Xue, Bui Cui:
ProjPert: Projection-Based Perturbation for Label Protection in Split Learning Based Vertical Federated Learning. IEEE Trans. Knowl. Data Eng. 36(7): 3417-3428 (2024)- [j13]Jiawei Jiang, Shaoduo Gan, Bo Du, Gustavo Alonso, Ana Klimovic, Ankit Singla, Wentao Wu, Sheng Wang, Ce Zhang:
A systematic evaluation of machine learning on serverless infrastructure. VLDB J. 33(2): 425-449 (2024) - [j12]Jiawei Jiang, Yi Wei, Yu Liu, Wentao Wu, Chuang Hu, Zhigao Zheng, Ziyi Zhang, Yingxia Shao, Ce Zhang:
How good are machine learning clouds? Benchmarking two snapshots over 5 years. VLDB J. 33(3): 833-857 (2024) - [j11]Lijie Xu, Shuang Qiu, Binhang Yuan, Jiawei Jiang, Cédric Renggli, Shaoduo Gan, Kaan Kara, Guoliang Li, Ji Liu, Wentao Wu, Jieping Ye, Ce Zhang:
Stochastic gradient descent without full data shuffle: with applications to in-database machine learning and deep learning systems. VLDB J. 33(5): 1231-1255 (2024) - [c37]Steve Rhyner, Haocong Luo, Juan Gómez-Luna, Mohammad Sadrosadati, Jiawei Jiang, Ataberk Olgun, Harshita Gupta, Ce Zhang, Onur Mutlu:
PIM-Opt: Demystifying Distributed Optimization Algorithms on a Real-World Processing-In-Memory System. PACT 2024: 201-218 - [c36]Hao Huang, Qian Yan, Keqi Han, Ting Gan, Jiawei Jiang, Quanqing Xu, Chuanhui Yang:
Learning Diffusions under Uncertainty. AAAI 2024: 20430-20437 - [c35]Xiaokai Zhou, Xiao Yan, Xinyan Li, Hao Huang, Quanqing Xu, Qinbo Zhang, Yen Jerome, Zhaohui Cai, Jiawei Jiang:
VFDV-IM: An Efficient and Securely Vertical Federated Data Valuation. DASFAA (1) 2024: 409-424 - [c34]Qinbo Zhang, Xiao Yan, Yukai Ding, Quanqing Xu, Chuang Hu, Xiaokai Zhou, Jiawei Jiang:
TreeCSS: An Efficient Framework for Vertical Federated Learning. DASFAA (1) 2024: 425-441 - [c33]Yuxuan Liang, Wentao Zhang, Zeang Sheng, Ling Yang, Jiawei Jiang, Yunhai Tong, Bin Cui:
HGAMLP: Heterogeneous Graph Attention MLP with De-Redundancy Mechanism. ICDE 2024: 2779-2791 - [c32]Yuxiang Wang, Xiao Yan, Chuang Hu, Quanqing Xu, Chuanhui Yang, Fangcheng Fu, Wentao Zhang, Hao Wang, Bo Du, Jiawei Jiang:
Generative and Contrastive Paradigms Are Complementary for Graph Self-Supervised Learning. ICDE 2024: 3364-3378 - [c31]Qiang Huang, Xin Wang, Susie Xi Rao, Zhichao Han, Zitao Zhang, Yongjun He, Quanqing Xu, Yang Zhao, Zhigao Zheng, Jiawei Jiang:
Benchtemp: A General Benchmark for Evaluating Temporal Graph Neural Networks. ICDE 2024: 4044-4057 - [c30]Yuxiang Wang, Xiao Yan, Shiyu Jin, Hao Huang, Quanqing Xu, Qingchen Zhang, Bo Du, Jiawei Jiang:
Self-Supervised Learning for Graph Dataset Condensation. KDD 2024: 3289-3298 - [i19]Chen Zhao, Ting Yu, Zhigao Zheng, Song Jin, Jiawei Jiang, Bo Du, Dacheng Tao:
PICO: Accelerating All k-Core Paradigms on GPU. CoRR abs/2402.15253 (2024) - [i18]Steve Rhyner, Haocong Luo, Juan Gómez-Luna, Mohammad Sadrosadati, Jiawei Jiang, Ataberk Olgun, Harshita Gupta, Ce Zhang, Onur Mutlu:
Analysis of Distributed Optimization Algorithms on a Real Processing-In-Memory System. CoRR abs/2404.07164 (2024) - [i17]Qinbo Zhang, Xiao Yan, Yukai Ding, Quanqing Xu, Chuang Hu, Xiaokai Zhou, Jiawei Jiang:
TreeCSS: An Efficient Framework for Vertical Federated Learning. CoRR abs/2408.01691 (2024) - [i16]Yuxiang Wang, Xiao Yan, Shiyu Jin, Quanqing Xu, Chuanhui Yang, Yuanyuan Zhu, Chuang Hu, Bo Du, Jiawei Jiang:
Hound: Hunting Supervision Signals for Few and Zero Shot Node Classification on Text-attributed Graph. CoRR abs/2409.00727 (2024) - [i15]Qiang Huang, Xiao Yan, Xin Wang, Susie Xi Rao, Zhichao Han, Fangcheng Fu, Wentao Zhang, Jiawei Jiang:
Retrofitting Temporal Graph Neural Networks with Transformer. CoRR abs/2409.05477 (2024) - 2023
- [j10]Xupeng Miao, Wentao Zhang, Yingxia Shao, Bin Cui, Lei Chen, Ce Zhang, Jiawei Jiang:
Lasagne: A Multi-Layer Graph Convolutional Network Framework via Node-Aware Deep Architecture. IEEE Trans. Knowl. Data Eng. 35(2): 1721-1733 (2023) - [i14]Qiang Huang, Jiawei Jiang, Susie Xi Rao, Ce Zhang, Zhichao Han, Zitao Zhang, Xin Wang, Yongjun He, Quanqing Xu, Yang Zhao, Chuang Hu, Shuo Shang, Bo Du:
BenchTemp: A General Benchmark for Evaluating Temporal Graph Neural Networks. CoRR abs/2308.16385 (2023) - [i13]Yuxiang Wang, Xiao Yan, Chuang Hu, Fangcheng Fu, Wentao Zhang, Hao Wang, Shuo Shang, Jiawei Jiang:
Generative and Contrastive Paradigms Are Complementary for Graph Self-Supervised Learning. CoRR abs/2310.15523 (2023) - [i12]Hao Huang, Qian Yan, Keqi Han, Ting Gan, Jiawei Jiang, Quanqing Xu, Chuanhui Yang:
Learning Diffusions under Uncertainty. CoRR abs/2312.07942 (2023) - 2022
- [b1]Jiawei Jiang, Bin Cui, Ce Zhang:
Distributed Machine Learning and Gradient Optimization. Springer 2022, ISBN 978-981-16-3419-2, pp. 1-169 - [j9]Fangcheng Fu, Xupeng Miao, Jiawei Jiang, Huanran Xue, Bin Cui:
Towards Communication-efficient Vertical Federated Learning Training via Cache-enabled Local Update. Proc. VLDB Endow. 15(10): 2111-2120 (2022) - [j8]Xupeng Miao, Lingxiao Ma, Zhi Yang, Yingxia Shao, Bin Cui, Lele Yu, Jiawei Jiang:
CuWide: Towards Efficient Flow-Based Training for Sparse Wide Models on GPUs. IEEE Trans. Knowl. Data Eng. 34(9): 4119-4132 (2022) - [c29]Mingxuan Lu, Zhichao Han, Susie Xi Rao, Zitao Zhang, Yang Zhao, Yinan Shan, Ramesh Raghunathan, Ce Zhang, Jiawei Jiang:
BRIGHT - Graph Neural Networks in Real-time Fraud Detection. CIKM 2022: 3342-3351 - [c28]Xupeng Miao, Wentao Zhang, Yingxia Shao, Bin Cui, Lei Chen, Ce Zhang, Jiawei Jiang:
Lasagne: A Multi-Layer Graph Convolutional Network Framework via Node-aware Deep Architecture (Extended Abstract). ICDE 2022: 1561-1562 - [c27]Jiawei Jiang, Yusong Hu, Xiaosen Li, Wen Ouyang, Zhitao Wang, Fangcheng Fu, Bin Cui:
Analyzing Online Transaction Networks with Network Motifs. KDD 2022: 3098-3106 - [c26]Jiawei Jiang, Lukas Burkhalter, Fangcheng Fu, Bolin Ding, Bo Du, Anwar Hithnawi, Bo Li, Ce Zhang:
VF-PS: How to Select Important Participants in Vertical Federated Learning, Efficiently and Securely? NeurIPS 2022 - [c25]Lijie Xu, Shuang Qiu, Binhang Yuan, Jiawei Jiang, Cédric Renggli, Shaoduo Gan, Kaan Kara, Guoliang Li, Ji Liu, Wentao Wu, Jieping Ye, Ce Zhang:
In-Database Machine Learning with CorgiPile: Stochastic Gradient Descent without Full Data Shuffle. SIGMOD Conference 2022: 1286-1300 - [i11]Mingxuan Lu, Zhichao Han, Susie Xi Rao, Zitao Zhang, Yang Zhao, Yinan Shan, Ramesh Raghunathan, Ce Zhang, Jiawei Jiang:
BRIGHT - Graph Neural Networks in Real-Time Fraud Detection. CoRR abs/2205.13084 (2022) - [i10]Lijie Xu, Shuang Qiu, Binhang Yuan, Jiawei Jiang, Cédric Renggli, Shaoduo Gan, Kaan Kara, Guoliang Li, Ji Liu, Wentao Wu, Jieping Ye, Ce Zhang:
Stochastic Gradient Descent without Full Data Shuffle. CoRR abs/2206.05830 (2022) - [i9]Fangcheng Fu, Xupeng Miao, Jiawei Jiang, Huanran Xue, Bin Cui:
Towards Communication-efficient Vertical Federated Learning Training via Cache-enabled Local Updates. CoRR abs/2207.14628 (2022) - 2021
- [j7]Yang Li, Yu Shen, Wentao Zhang, Jiawei Jiang, Yaliang Li, Bolin Ding, Jingren Zhou, Zhi Yang, Wentao Wu, Ce Zhang, Bin Cui:
VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition. Proc. VLDB Endow. 14(11): 2167-2176 (2021) - [j6]Shaoduo Gan, Xiangru Lian, Rui Wang, Jianbin Chang, Chengjun Liu, Hongmei Shi, Shengzhuo Zhang, Xianghong Li, Tengxu Sun, Jiawei Jiang, Binhang Yuan, Sen Yang, Ji Liu, Ce Zhang:
BAGUA: Scaling up Distributed Learning with System Relaxations. Proc. VLDB Endow. 15(4): 804-813 (2021) - [j5]Yunyan Guo, Zhipeng Zhang, Jiawei Jiang, Wentao Wu, Ce Zhang, Bin Cui, Jianzhong Li:
Model averaging in distributed machine learning: a case study with Apache Spark. VLDB J. 30(4): 693-712 (2021) - [c24]Yang Li, Yu Shen, Jiawei Jiang, Jinyang Gao, Ce Zhang, Bin Cui:
MFES-HB: Efficient Hyperband with Multi-Fidelity Quality Measurements. AAAI 2021: 8491-8500 - [c23]Leonel Aguilar Melgar, David Dao, Shaoduo Gan, Nezihe Merve Gürel, Nora Hollenstein, Jiawei Jiang, Bojan Karlas, Thomas Lemmin, Tian Li, Yang Li, Susie Xi Rao, Johannes Rausch, Cédric Renggli, Luka Rimanic, Maurice Weber, Shuai Zhang, Zhikuan Zhao, Kevin Schawinski, Wentao Wu, Ce Zhang:
Ease.ML: A Lifecycle Management System for Machine Learning. CIDR 2021 - [c22]Xupeng Miao, Lingxiao Ma, Zhi Yang, Yingxia Shao, Bin Cui, Lele Yu, Jiawei Jiang:
CuWide: Towards Efficient Flow-based Training for Sparse Wide Models on GPUs (Extended Abstract). ICDE 2021: 2330-2331 - [c21]Yang Li, Yu Shen, Wentao Zhang, Yuanwei Chen, Huaijun Jiang, Mingchao Liu, Jiawei Jiang, Jinyang Gao, Wentao Wu, Zhi Yang, Ce Zhang, Bin Cui:
OpenBox: A Generalized Black-box Optimization Service. KDD 2021: 3209-3219 - [c20]Fangcheng Fu, Yingxia Shao, Lele Yu, Jiawei Jiang, Huanran Xue, Yangyu Tao, Bin Cui:
VF2Boost: Very Fast Vertical Federated Gradient Boosting for Cross-Enterprise Learning. SIGMOD Conference 2021: 563-576 - [c19]Jiawei Jiang, Shaoduo Gan, Yue Liu, Fanlin Wang, Gustavo Alonso, Ana Klimovic, Ankit Singla, Wentao Wu, Ce Zhang:
Towards Demystifying Serverless Machine Learning Training. SIGMOD Conference 2021: 857-871 - [c18]Xupeng Miao, Xiaonan Nie, Yingxia Shao, Zhi Yang, Jiawei Jiang, Lingxiao Ma, Bin Cui:
Heterogeneity-Aware Distributed Machine Learning Training via Partial Reduce. SIGMOD Conference 2021: 2262-2270 - [i8]Jiawei Jiang, Shaoduo Gan, Yue Liu, Fanlin Wang, Gustavo Alonso, Ana Klimovic, Ankit Singla, Wentao Wu, Ce Zhang:
Towards Demystifying Serverless Machine Learning Training. CoRR abs/2105.07806 (2021) - [i7]Yang Li, Yu Shen, Wentao Zhang, Yuanwei Chen, Huaijun Jiang, Mingchao Liu, Jiawei Jiang, Jinyang Gao, Wentao Wu, Zhi Yang, Ce Zhang, Bin Cui:
OpenBox: A Generalized Black-box Optimization Service. CoRR abs/2106.00421 (2021) - [i6]Shaoduo Gan, Xiangru Lian, Rui Wang, Jianbin Chang, Chengjun Liu, Hongmei Shi, Shengzhuo Zhang, Xianghong Li, Tengxu Sun, Jiawei Jiang, Binhang Yuan, Sen Yang, Ji Liu, Ce Zhang:
BAGUA: Scaling up Distributed Learning with System Relaxations. CoRR abs/2107.01499 (2021) - [i5]Yang Li, Yu Shen, Wentao Zhang, Jiawei Jiang, Bolin Ding, Yaliang Li, Jingren Zhou, Zhi Yang, Wentao Wu, Ce Zhang, Bin Cui:
VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition. CoRR abs/2107.08861 (2021) - [i4]Wentao Zhang, Jiawei Jiang, Yingxia Shao, Bin Cui:
Efficient Diversity-Driven Ensemble for Deep Neural Networks. CoRR abs/2112.13316 (2021) - 2020
- [j4]Wentao Zhang, Jiawei Jiang, Yingxia Shao, Bin Cui:
Snapshot boosting: a fast ensemble framework for deep neural networks. Sci. China Inf. Sci. 63(1): 112102 (2020) - [j3]Jiawei Jiang, Fangcheng Fu, Tong Yang, Yingxia Shao, Bin Cui:
SKCompress: compressing sparse and nonuniform gradient in distributed machine learning. VLDB J. 29(5): 945-972 (2020) - [c17]Yang Li, Jiawei Jiang, Jinyang Gao, Yingxia Shao, Ce Zhang, Bin Cui:
Efficient Automatic CASH via Rising Bandits. AAAI 2020: 4763-4771 - [c16]Wentao Zhang, Jiawei Jiang, Yingxia Shao, Bin Cui:
Efficient Diversity-Driven Ensemble for Deep Neural Networks. ICDE 2020: 73-84 - [c15]Zhipeng Zhang, Wentao Wu, Jiawei Jiang, Lele Yu, Bin Cui, Ce Zhang:
C olumnSGD: A Column-oriented Framework for Distributed Stochastic Gradient Descent. ICDE 2020: 1513-1524 - [c14]Jiawei Jiang, Pin Xiao, Lele Yu, Xiaosen Li, Jiefeng Cheng, Xupeng Miao, Zhipeng Zhang, Bin Cui:
PSGraph: How Tencent trains extremely large-scale graphs with Spark? ICDE 2020: 1549-1557 - [c13]Fangcheng Fu, Yuzheng Hu, Yihan He, Jiawei Jiang, Yingxia Shao, Ce Zhang, Bin Cui:
Don't Waste Your Bits! Squeeze Activations and Gradients for Deep Neural Networks via TinyScript. ICML 2020: 3304-3314 - [c12]Wentao Zhang, Xupeng Miao, Yingxia Shao, Jiawei Jiang, Lei Chen, Olivier Ruas, Bin Cui:
Reliable Data Distillation on Graph Convolutional Network. SIGMOD Conference 2020: 1399-1414 - [i3]Yang Li, Yu Shen, Jiawei Jiang, Jinyang Gao, Ce Zhang, Bin Cui:
MFES-HB: Efficient Hyperband with Multi-Fidelity Quality Measurements. CoRR abs/2012.03011 (2020) - [i2]Yang Li, Jiawei Jiang, Jinyang Gao, Yingxia Shao, Ce Zhang, Bin Cui:
Efficient Automatic CASH via Rising Bandits. CoRR abs/2012.04371 (2020)
2010 – 2019
- 2019
- [j2]Fangcheng Fu, Jiawei Jiang, Yingxia Shao, Bin Cui:
An Experimental Evaluation of Large Scale GBDT Systems. Proc. VLDB Endow. 12(11): 1357-1370 (2019) - [c11]Huanran Xue, Jiawei Jiang, Yingxia Shao, Bin Cui:
FeatureBand: A Feature Selection Method by Combining Early Stopping and Genetic Local Search. APWeb/WAIM (2) 2019: 27-41 - [c10]Haobo Sun, Yingxia Shao, Jiawei Jiang, Bin Cui, Kai Lei, Yu Xu, Jiang Wang:
Sparse Gradient Compression for Distributed SGD. DASFAA (2) 2019: 139-155 - [c9]Zhipeng Zhang, Jiawei Jiang, Wentao Wu, Ce Zhang, Lele Yu, Bin Cui:
MLlib*: Fast Training of GLMs Using Spark MLlib. ICDE 2019: 1778-1789 - [c8]Zhipeng Zhang, Bin Cui, Yingxia Shao, Lele Yu, Jiawei Jiang, Xupeng Miao:
PS2: Parameter Server on Spark. SIGMOD Conference 2019: 376-388 - [i1]Fangcheng Fu, Jiawei Jiang, Yingxia Shao, Bin Cui:
An Experimental Evaluation of Large Scale GBDT Systems. CoRR abs/1907.01882 (2019) - 2018
- [c7]Jiawei Jiang, Fangcheng Fu, Tong Yang, Bin Cui:
SketchML: Accelerating Distributed Machine Learning with Data Sketches. SIGMOD Conference 2018: 1269-1284 - [c6]Jiawei Jiang, Bin Cui, Ce Zhang, Fangcheng Fu:
DimBoost: Boosting Gradient Boosting Decision Tree to Higher Dimensions. SIGMOD Conference 2018: 1363-1376 - 2017
- [j1]Jiawei Jiang, Yunhai Tong, Hua Lu, Bin Cui, Kai Lei, Lele Yu:
GVoS: A General System for Near-Duplicate Video-Related Applications on Storm. ACM Trans. Inf. Syst. 36(1): 3:1-3:36 (2017) - [c5]Jiawei Jiang, Ming Huang, Jie Jiang, Bin Cui:
TeslaML: Steering Machine Learning Automatically in Tencent. APWeb/WAIM (2) 2017: 313-318 - [c4]Jiawei Jiang, Zhipeng Zhang, Bin Cui, Yunhai Tong, Ning Xu:
StroMAX: Partitioning-Based Scheduler for Real-Time Stream Processing System. DASFAA (2) 2017: 269-288 - [c3]Jie Jiang, Jiawei Jiang, Bin Cui, Ce Zhang:
TencentBoost: A Gradient Boosting Tree System with Parameter Server. ICDE 2017: 281-284 - [c2]Jiawei Jiang, Bin Cui, Ce Zhang, Lele Yu:
Heterogeneity-aware Distributed Parameter Servers. SIGMOD Conference 2017: 463-478 - 2013
- [c1]Jiawei Jiang, Haojiang Deng, Xue Liu:
A predictive dynamic load balancing algorithm with service differentiation. ICCT 2013: 372-377
Coauthor Index
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