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Ji Liu 0003
Person information
- affiliation: Hithink RoyalFlush Information Network Co., Ltd., China
- affiliation: Baidu Inc., Baidu Research, Beijing, China
- affiliation (2013-2017): MSR - Inria Joint Centre, INRIA Sophia-Antipolis Méditerranée, LIRMM, France
- affiliation (2013-2017): University of Montpellier, France
Other persons with the same name
- Ji Liu — disambiguation page
- Ji Liu 0001 — Stony Brook University, NY, USA (and 2 more)
- Ji Liu 0002 — Kwai Inc., Seattle AI Lab, WA, USA (and 5 more)
- Ji Liu 0004 — Pennsylvania State University, Department of Mechanical and Nuclear Engineering, University Park, PA, USA
- Ji Liu 0005 — University of Science and Technology Beijing, School of Computer and Communication Engineering, China (and 1 more)
- Ji Liu 0006 — Chongqing University, College of Computer Science, China
- Ji Liu 0007 — Argonne National Laboratory, USA
- Ji Liu 0008 — ShanghaiTech University, Shanghai, China
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2020 – today
- 2025
- [j24]Miaoyu Li, Ying Fu, Tao Zhang, Ji Liu, Dejing Dou, Chenggang Yan, Yulun Zhang:
Latent Diffusion Enhanced Rectangle Transformer for Hyperspectral Image Restoration. IEEE Trans. Pattern Anal. Mach. Intell. 47(1): 549-564 (2025) - 2024
- [j23]Qilong Li, Ji Liu, Yifan Sun, Chongsheng Zhang, Dejing Dou:
On mask-based image set desensitization with recognition support. Appl. Intell. 54(11-12): 886-898 (2024) - [j22]Juncheng Jia, Ji Liu, Chendi Zhou, Hao Tian, Mianxiong Dong, Dejing Dou:
Efficient asynchronous federated learning with sparsification and quantization. Concurr. Comput. Pract. Exp. 36(9) (2024) - [j21]Ji Liu, Chunlu Chen, Yu Li, Lin Sun, Yulun Song, Jingbo Zhou, Bo Jing, Dejing Dou:
Enhancing trust and privacy in distributed networks: a comprehensive survey on blockchain-based federated learning. Knowl. Inf. Syst. 66(8): 4377-4403 (2024) - [c36]Ji Liu, Juncheng Jia, Tianshi Che, Chao Huo, Jiaxiang Ren, Yang Zhou, Huaiyu Dai, Dejing Dou:
FedASMU: Efficient Asynchronous Federated Learning with Dynamic Staleness-Aware Model Update. AAAI 2024: 13900-13908 - [c35]Xuhong Li, Haoyi Xiong, Xingjian Li, Xiao Zhang, Ji Liu, Haiyan Jiang, Zeyu Chen, Dejing Dou:
G-LIME: Statistical Learning for Local Interpretations of Deep Neural Networks Using Global Priors (Abstract Reprint). AAAI 2024: 22705 - [c34]Ji Liu, Jiaxiang Ren, Ruoming Jin, Zijie Zhang, Yang Zhou, Patrick Valduriez, Dejing Dou:
Fisher Information-based Efficient Curriculum Federated Learning with Large Language Models. EMNLP 2024: 10497-10523 - [c33]Ji Liu, Tianshi Che, Yang Zhou, Ruoming Jin, Huaiyu Dai, Dejing Dou, Patrick Valduriez:
AEDFL: Efficient Asynchronous Decentralized Federated Learning with Heterogeneous Devices. SDM 2024: 833-841 - [i31]Ji Liu, Chunlu Chen, Yu Li, Lin Sun, Yulun Song, Jingbo Zhou, Bo Jing, Dejing Dou:
Enhancing Trust and Privacy in Distributed Networks: A Comprehensive Survey on Blockchain-based Federated Learning. CoRR abs/2403.19178 (2024) - [i30]Chongsheng Zhang, George Almpanidis, Gaojuan Fan, Binquan Deng, Yanbo Zhang, Ji Liu, Aouaidjia Kamel, Paolo Soda, João Gama:
A Systematic Review on Long-Tailed Learning. CoRR abs/2408.00483 (2024) - [i29]Ji Liu, Juncheng Jia, Hong Zhang, Yuhui Yun, Leye Wang, Yang Zhou, Huaiyu Dai, Dejing Dou:
Efficient Federated Learning Using Dynamic Update and Adaptive Pruning with Momentum on Shared Server Data. CoRR abs/2408.05678 (2024) - [i28]Ji Liu, Jiaxiang Ren, Ruoming Jin, Zijie Zhang, Yang Zhou, Patrick Valduriez, Dejing Dou:
Fisher Information-based Efficient Curriculum Federated Learning with Large Language Models. CoRR abs/2410.00131 (2024) - [i27]Chunlu Chen, Ji Liu, Haowen Tan, Xingjian Li, Kevin I-Kai Wang, Peng Li, Kouichi Sakurai, Dejing Dou:
Trustworthy Federated Learning: Privacy, Security, and Beyond. CoRR abs/2411.01583 (2024) - 2023
- [j20]Xuhong Li, Haoyi Xiong, Xingjian Li, Xiao Zhang, Ji Liu, Haiyan Jiang, Zeyu Chen, Dejing Dou:
G-LIME: Statistical learning for local interpretations of deep neural networks using global priors. Artif. Intell. 314: 103823 (2023) - [j19]Ji Liu, Xuehai Zhou, Lei Mo, Shilei Ji, Yuan Liao, Zheng Li, Qin Gu, Dejing Dou:
Distributed and deep vertical federated learning with big data. Concurr. Comput. Pract. Exp. 35(21) (2023) - [j18]Ji Liu, Daxiang Dong, Xi Wang, An Qin, Xingjian Li, Patrick Valduriez, Dejing Dou, Dianhai Yu:
Large-scale knowledge distillation with elastic heterogeneous computing resources. Concurr. Comput. Pract. Exp. 35(26) (2023) - [j17]Ji Liu, Zhihua Wu, Danlei Feng, Minxu Zhang, Xinxuan Wu, Xuefeng Yao, Dianhai Yu, Yanjun Ma, Feng Zhao, Dejing Dou:
HeterPS: Distributed deep learning with reinforcement learning based scheduling in heterogeneous environments. Future Gener. Comput. Syst. 148: 106-117 (2023) - [j16]Ji Liu, Lei Mo, Sijia Yang, Jingbo Zhou, Shilei Ji, Haoyi Xiong, Dejing Dou:
Data Placement for Multi-Tenant Data Federation on the Cloud. IEEE Trans. Cloud Comput. 11(2): 1414-1429 (2023) - [j15]Ji Liu, Juncheng Jia, Beichen Ma, Chendi Zhou, Jingbo Zhou, Yang Zhou, Huaiyu Dai, Dejing Dou:
Multi-Job Intelligent Scheduling With Cross-Device Federated Learning. IEEE Trans. Parallel Distributed Syst. 34(2): 535-551 (2023) - [c32]Chongsheng Zhang, Yaxin Hou, Ke Chen, Shuang Cao, Gaojuan Fan, Ji Liu:
Quality-Aware Self-Training on Differentiable Synthesis of Rare Relational Data. AAAI 2023: 6602-6611 - [c31]Miaoyu Li, Ji Liu, Ying Fu, Yulun Zhang, Dejing Dou:
Spectral Enhanced Rectangle Transformer for Hyperspectral Image Denoising. CVPR 2023: 5805-5814 - [c30]Zichun Wang, Ying Fu, Ji Liu, Yulun Zhang:
LG-BPN: Local and Global Blind-Patch Network for Self-Supervised Real-World Denoising. CVPR 2023: 18156-18165 - [c29]Tianshi Che, Ji Liu, Yang Zhou, Jiaxiang Ren, Jiwen Zhou, Victor S. Sheng, Huaiyu Dai, Dejing Dou:
Federated Learning of Large Language Models with Parameter-Efficient Prompt Tuning and Adaptive Optimization. EMNLP 2023: 7871-7888 - [c28]Yiming Zhao, Lei Mo, Ji Liu:
Path Planning Based on Traffic Flow Prediction for Vehicle Scheduling. ICCC 2023: 1-5 - [c27]Miaoyu Li, Ying Fu, Ji Liu, Yulun Zhang:
Pixel Adaptive Deep Unfolding Transformer for Hyperspectral Image Reconstruction. ICCV 2023: 12913-12922 - [c26]Derong Xu, Jingbo Zhou, Tong Xu, Yuan Xia, Ji Liu, Enhong Chen, Dejing Dou:
Multimodal Biological Knowledge Graph Completion via Triple Co-Attention Mechanism. ICDE 2023: 3928-3941 - [c25]Tianshi Che, Yang Zhou, Zijie Zhang, Lingjuan Lyu, Ji Liu, Da Yan, Dejing Dou, Jun Huan:
Fast Federated Machine Unlearning with Nonlinear Functional Theory. ICML 2023: 4241-4268 - [c24]Xinbiao Gan, Guang Wu, Ruigeng Zeng, Jiaqi Si, Ji Liu, Daxiang Dong, Chunye Gong, Cong Liu, Tiejun Li:
FT-topo: Architecture-Driven Folded-Triangle Partitioning for Communication-efficient Graph Processing. ICS 2023: 240-250 - [c23]Shuangli Li, Jingbo Zhou, Ji Liu, Tong Xu, Enhong Chen, Hui Xiong:
Multi-Temporal Relationship Inference in Urban Areas. KDD 2023: 1316-1327 - [i26]Ji Liu, Xuehai Zhou, Lei Mo, Shilei Ji, Yuan Liao, Zheng Li, Qin Gu, Dejing Dou:
Distributed and Deep Vertical Federated Learning with Big Data. CoRR abs/2303.04574 (2023) - [i25]Zichun Wang, Ying Fu, Ji Liu, Yulun Zhang:
LG-BPN: Local and Global Blind-Patch Network for Self-Supervised Real-World Denoising. CoRR abs/2304.00534 (2023) - [i24]Miaoyu Li, Ji Liu, Ying Fu, Yulun Zhang, Dejing Dou:
Spectral Enhanced Rectangle Transformer for Hyperspectral Image Denoising. CoRR abs/2304.00844 (2023) - [i23]Shuangli Li, Jingbo Zhou, Ji Liu, Tong Xu, Enhong Chen, Hui Xiong:
Multi-Temporal Relationship Inference in Urban Areas. CoRR abs/2306.08921 (2023) - [i22]Miaoyu Li, Ying Fu, Ji Liu, Yulun Zhang:
Pixel Adaptive Deep Unfolding Transformer for Hyperspectral Image Reconstruction. CoRR abs/2308.10820 (2023) - [i21]Tianshi Che, Ji Liu, Yang Zhou, Jiaxiang Ren, Jiwen Zhou, Victor S. Sheng, Huaiyu Dai, Dejing Dou:
Federated Learning of Large Language Models with Parameter-Efficient Prompt Tuning and Adaptive Optimization. CoRR abs/2310.15080 (2023) - [i20]Ji Liu, Juncheng Jia, Tianshi Che, Chao Huo, Jiaxiang Ren, Yang Zhou, Huaiyu Dai, Dejing Dou:
FedASMU: Efficient Asynchronous Federated Learning with Dynamic Staleness-aware Model Update. CoRR abs/2312.05770 (2023) - [i19]Qilong Li, Ji Liu, Yifan Sun, Chongsheng Zhang, Dejing Dou:
On Mask-based Image Set Desensitization with Recognition Support. CoRR abs/2312.08975 (2023) - [i18]Ji Liu, Tianshi Che, Yang Zhou, Ruoming Jin, Huaiyu Dai, Dejing Dou, Patrick Valduriez:
AEDFL: Efficient Asynchronous Decentralized Federated Learning with Heterogeneous Devices. CoRR abs/2312.10935 (2023) - [i17]Juncheng Jia, Ji Liu, Chendi Zhou, Hao Tian, Mianxiong Dong, Dejing Dou:
Efficient Asynchronous Federated Learning with Sparsification and Quantization. CoRR abs/2312.15186 (2023) - 2022
- [j14]Ji Liu, Jizhou Huang, Yang Zhou, Xuhong Li, Shilei Ji, Haoyi Xiong, Dejing Dou:
From distributed machine learning to federated learning: a survey. Knowl. Inf. Syst. 64(4): 885-917 (2022) - [j13]Xuhong Li, Haoyi Xiong, Xingjian Li, Xuanyu Wu, Xiao Zhang, Ji Liu, Jiang Bian, Dejing Dou:
Interpretable deep learning: interpretation, interpretability, trustworthiness, and beyond. Knowl. Inf. Syst. 64(12): 3197-3234 (2022) - [j12]Chongsheng Zhang, Yuefeng Tao, Kai Du, Weiping Ding, Bin Wang, Ji Liu, Wei Wang:
Character-Level Street View Text Spotting Based on Deep Multisegmentation Network for Smarter Autonomous Driving. IEEE Trans. Artif. Intell. 3(2): 297-308 (2022) - [j11]Ji Liu, Carlyna Bondiombouy, Lei Mo, Patrick Valduriez:
Two-Phase Scheduling for Efficient Vehicle Sharing. IEEE Trans. Intell. Transp. Syst. 23(1): 457-470 (2022) - [j10]Xingjian Li, Haoyi Xiong, Zeyu Chen, Jun Huan, Ji Liu, Cheng-Zhong Xu, Dejing Dou:
Knowledge Distillation with Attention for Deep Transfer Learning of Convolutional Networks. ACM Trans. Knowl. Discov. Data 16(3): 42:1-42:20 (2022) - [c22]Chendi Zhou, Ji Liu, Juncheng Jia, Jingbo Zhou, Yang Zhou, Huaiyu Dai, Dejing Dou:
Efficient Device Scheduling with Multi-Job Federated Learning. AAAI 2022: 9971-9979 - [c21]Lei Mo, Qi Zhou, Angeliki Kritikakou, Ji Liu:
Energy Efficient, Real-time and Reliable Task Deployment on NoC-based Multicores with DVFS. DATE 2022: 1347-1352 - [c20]Tianshi Che, Zijie Zhang, Yang Zhou, Xin Zhao, Ji Liu, Zhe Jiang, Da Yan, Ruoming Jin, Dejing Dou:
Federated Fingerprint Learning with Heterogeneous Architectures. ICDM 2022: 31-40 - [c19]Jiayin Jin, Jiaxiang Ren, Yang Zhou, Lingjuan Lyu, Ji Liu, Dejing Dou:
Accelerated Federated Learning with Decoupled Adaptive Optimization. ICML 2022: 10298-10322 - [c18]Guanghao Li, Yue Hu, Miao Zhang, Ji Liu, Quanjun Yin, Yong Peng, Dejing Dou:
FedHiSyn: A Hierarchical Synchronous Federated Learning Framework for Resource and Data Heterogeneity. ICPP 2022: 8:1-8:11 - [c17]Hong Zhang, Ji Liu, Juncheng Jia, Yang Zhou, Huaiyu Dai, Dejing Dou:
FedDUAP: Federated Learning with Dynamic Update and Adaptive Pruning Using Shared Data on the Server. IJCAI 2022: 2776-2782 - [i16]Hong Zhang, Ji Liu, Juncheng Jia, Yang Zhou, Huaiyu Dai, Dejing Dou:
FedDUAP: Federated Learning with Dynamic Update and Adaptive Pruning Using Shared Data on the Server. CoRR abs/2204.11536 (2022) - [i15]Guanghao Li, Yue Hu, Miao Zhang, Ji Liu, Quanjun Yin, Yong Peng, Dejing Dou:
FedHiSyn: A Hierarchical Synchronous Federated Learning Framework for Resource and Data Heterogeneity. CoRR abs/2206.10546 (2022) - [i14]Ji Liu, Daxiang Dong, Xi Wang, An Qin, Xingjian Li, Patrick Valduriez, Dejing Dou, Dianhai Yu:
Large-scale Knowledge Distillation with Elastic Heterogeneous Computing Resources. CoRR abs/2207.06667 (2022) - [i13]Jiayin Jin, Jiaxiang Ren, Yang Zhou, Lingjuan Lyu, Ji Liu, Dejing Dou:
Accelerated Federated Learning with Decoupled Adaptive Optimization. CoRR abs/2207.07223 (2022) - [i12]Ji Liu, Juncheng Jia, Beichen Ma, Chendi Zhou, Jingbo Zhou, Yang Zhou, Huaiyu Dai, Dejing Dou:
Multi-Job Intelligent Scheduling with Cross-Device Federated Learning. CoRR abs/2211.13430 (2022) - 2021
- [j9]Xingjian Li, Dou Goodman, Ji Liu, Tao Wei, Dejing Dou:
Improving Adversarial Robustness via Attention and Adversarial Logit Pairing. Frontiers Artif. Intell. 4: 752831 (2021) - [j8]Haiyan Jiang, Haoyi Xiong, Dongrui Wu, Ji Liu, Dejing Dou:
AgFlow: fast model selection of penalized PCA via implicit regularization effects of gradient flow. Mach. Learn. 110(8): 2131-2150 (2021) - [c16]Congxi Xiao, Jingbo Zhou, Jizhou Huang, An Zhuo, Ji Liu, Haoyi Xiong, Dejing Dou:
C-Watcher: A Framework for Early Detection of High-Risk Neighborhoods Ahead of COVID-19 Outbreak. AAAI 2021: 4892-4900 - [c15]Daxiang Dong, Ji Liu, Xi Wang, Weibao Gong, An Qin, Xingjian Li, Dianhai Yu, Patrick Valduriez, Dejing Dou:
Elastic Deep Learning Using Knowledge Distillation with Heterogeneous Computing Resources. Euro-Par Workshops 2021: 116-128 - [c14]Ji Liu, Haoyi Xiong, Xiakai Wang, Jizhou Huang, Qiaojun Li, Tongtong Huang, Siyu Huang, Haifeng Wang, Dejing Dou:
An Investigation of Containment Measure Implementation and Public Responses to the COVID-19 Pandemic in Mainland China. ICDH 2021: 234-243 - [c13]Yue Li, Abdulhalim Dandoush, Ji Liu:
Evaluation and Optimization of learning-based DNS over HTTPS Traffic Classification. ISNCC 2021: 1-6 - [c12]Weijia Zhang, Hao Liu, Lijun Zha, Hengshu Zhu, Ji Liu, Dejing Dou, Hui Xiong:
MugRep: A Multi-Task Hierarchical Graph Representation Learning Framework for Real Estate Appraisal. KDD 2021: 3937-3947 - [c11]Zeru Zhang, Jiayin Jin, Zijie Zhang, Yang Zhou, Xin Zhao, Jiaxiang Ren, Ji Liu, Lingfei Wu, Ruoming Jin, Dejing Dou:
Validating the Lottery Ticket Hypothesis with Inertial Manifold Theory. NeurIPS 2021: 30196-30210 - [i11]Xuhong Li, Haoyi Xiong, Xingjian Li, Xuanyu Wu, Xiao Zhang, Ji Liu, Jiang Bian, Dejing Dou:
Interpretable Deep Learning: Interpretations, Interpretability, Trustworthiness, and Beyond. CoRR abs/2103.10689 (2021) - [i10]Ji Liu, Jizhou Huang, Yang Zhou, Xuhong Li, Shilei Ji, Haoyi Xiong, Dejing Dou:
From Distributed Machine Learning to Federated Learning: A Survey. CoRR abs/2104.14362 (2021) - [i9]Weijia Zhang, Hao Liu, Lijun Zha, Hengshu Zhu, Ji Liu, Dejing Dou, Hui Xiong:
MugRep: A Multi-Task Hierarchical Graph Representation Learning Framework for Real Estate Appraisal. CoRR abs/2107.05180 (2021) - [i8]Haiyan Jiang, Haoyi Xiong, Dongrui Wu, Ji Liu, Dejing Dou:
AgFlow: Fast Model Selection of Penalized PCA via Implicit Regularization Effects of Gradient Flow. CoRR abs/2110.03273 (2021) - [i7]Ji Liu, Zhihua Wu, Dianhai Yu, Yanjun Ma, Danlei Feng, Minxu Zhang, Xinxuan Wu, Xuefeng Yao, Dejing Dou:
HeterPS: Distributed Deep Learning With Reinforcement Learning Based Scheduling in Heterogeneous Environments. CoRR abs/2111.10635 (2021) - [i6]Chendi Zhou, Ji Liu, Juncheng Jia, Jingbo Zhou, Yang Zhou, Huaiyu Dai, Dejing Dou:
Efficient Device Scheduling with Multi-Job Federated Learning. CoRR abs/2112.05928 (2021) - [i5]Ji Liu, Lei Mo, Sijia Yang, Jingbo Zhou, Shilei Ji, Haoyi Xiong, Dejing Dou:
Data Placement for Multi-Tenant Data Federation on the Cloud. CoRR abs/2112.07980 (2021) - 2020
- [j7]Noel Moreno Lemus, Fábio Porto, Yania Molina Souto, Rafael S. Pereira, Ji Liu, Esther Pacciti, Patrick Valduriez:
SUQ2: Uncertainty Quantification Queries over Large Spatio-temporal Simulations. IEEE Data Eng. Bull. 43(1): 47-59 (2020) - [j6]Ji Liu, Noel Moreno Lemus, Esther Pacitti, Fábio Porto, Patrick Valduriez:
Parallel computation of PDFs on big spatial data using Spark. Distributed Parallel Databases 38(1): 63-100 (2020) - [c10]Qi Kang, Ji Liu, Sijia Yang, Haoyi Xiong, Haozhe An, Xingjian Li, Zhi Feng, Licheng Wang, Dejing Dou:
Quasi-optimal Data Placement for Secure Multi-tenant Data Federation on the Cloud. IEEE BigData 2020: 1954-1963 - [c9]Ji Liu, Xiakai Wang, Haoyi Xiong, Jizhou Huang, Siyu Huang, Haozhe An, Dejing Dou, Haifeng Wang:
An Investigation of Containment Measures Against the COVID-19 Pandemic in Mainland China. IEEE BigData 2020: 3204-3211 - [i4]Ji Liu, Xiakai Wang, Haoyi Xiong, Jizhou Huang, Siyu Huang, Haozhe An, Dejing Dou, Haifeng Wang:
An Investigation of Containment Measures Against the COVID-19 Pandemic in Mainland China. CoRR abs/2007.08254 (2020) - [i3]Congxi Xiao, Jingbo Zhou, Jizhou Huang, An Zhuo, Ji Liu, Haoyi Xiong, Dejing Dou:
C-Watcher: A Framework for Early Detection of High-Risk Neighborhoods Ahead of COVID-19 Outbreak. CoRR abs/2012.12169 (2020)
2010 – 2019
- 2019
- [b2]Daniel C. M. de Oliveira, Ji Liu, Esther Pacitti:
Data-Intensive Workflow Management: For Clouds and Data-Intensive and Scalable Computing Environments. Synthesis Lectures on Data Management, Morgan & Claypool Publishers 2019, ISBN 978-3-031-00744-6 - [j5]Ji Liu, Luis Pineda-Morales, Esther Pacitti, Alexandru Costan, Patrick Valduriez, Gabriel Antoniu, Marta Mattoso:
Efficient Scheduling of Scientific Workflows Using Hot Metadata in a Multisite Cloud. IEEE Trans. Knowl. Data Eng. 31(10): 1940-1953 (2019) - [i2]Dou Goodman, Xingjian Li, Ji Liu, Dejing Dou, Tao Wei:
Improving Adversarial Robustness via Attention and Adversarial Logit Pairing. CoRR abs/1908.11435 (2019) - 2018
- [j4]Ji Liu, Esther Pacitti, Patrick Valduriez:
A survey of scheduling frameworks in big data systems. Int. J. Cloud Comput. 7(2): 103-128 (2018) - [c8]Patrick Valduriez, Marta Mattoso, Reza Akbarinia, Heraldo Borges, José J. Camata, Alvaro L. G. A. Coutinho, Daniel Gaspar, Noel Moreno Lemus, Ji Liu, Hermano Lustosa, Florent Masseglia, Fabrício Nogueira da Silva, Vítor Silva, Renan Souza, Kary A. C. S. Ocaña, Eduardo S. Ogasawara, Daniel de Oliveira, Esther Pacitti, Fábio Porto, Dennis E. Shasha:
Scientific Data Analysis Using Data-Intensive Scalable Computing: The SciDISC Project. LADaS@VLDB 2018: 1-8 - [c7]Ji Liu, Noel Moreno Lemus, Esther Pacitti, Fábio Porto, Patrick Valduriez:
Computation of PDFs on Big Spatial Data: Problem & Architecture. LADaS@VLDB 2018: 80-83 - [i1]Ji Liu, Noel Moreno Lemus, Esther Pacitti, Fábio Porto, Patrick Valduriez:
Parallel Computation of PDFs on Big Spatial Data Using Spark. CoRR abs/1805.03141 (2018) - 2017
- [j3]Ji Liu, Esther Pacitti, Patrick Valduriez, Marta Mattoso:
Scientific Workflow Scheduling with Provenance Data in a Multisite Cloud. Trans. Large Scale Data Knowl. Centered Syst. 33: 80-112 (2017) - 2016
- [b1]Ji Liu:
Multisite Management of Scientific Workflows in the Cloud. (Gestion multisite de workflows scientifiques dans le cloud). University of Montpellier, France, 2016 - [j2]Ji Liu, Esther Pacitti, Patrick Valduriez, Daniel de Oliveira, Marta Mattoso:
Multi-objective scheduling of Scientific Workflows in multisite clouds. Future Gener. Comput. Syst. 63: 76-95 (2016) - [c6]Luis Pineda-Morales, Ji Liu, Alexandru Costan, Esther Pacitti, Gabriel Antoniu, Patrick Valduriez, Marta Mattoso:
Managing hot metadata for scientific workflows on multisite clouds. IEEE BigData 2016: 390-397 - [c5]Ji Liu, Esther Pacitti, Patrick Valduriez, Marta Mattoso:
Scientific Workflow Scheduling with Provenance Support in Multisite Cloud. VECPAR 2016: 206-219 - 2015
- [j1]Ji Liu, Esther Pacitti, Patrick Valduriez, Marta Mattoso:
A Survey of Data-Intensive Scientific Workflow Management. J. Grid Comput. 13(4): 457-493 (2015) - 2014
- [c4]Ji Liu, Vítor Silva, Esther Pacitti, Patrick Valduriez, Marta Mattoso:
Scientific Workflow Partitioning in Multisite Cloud. Euro-Par Workshops (1) 2014: 105-116 - 2012
- [c3]Zhenzhen Zhao, Ji Liu, Noël Crespi:
Dig-event: let's socialize around events. CSCW (Companion) 2012: 279-280 - 2011
- [c2]Zhenzhen Zhao, Sirsha Bhattarai, Ji Liu, Noël Crespi:
Mashup services to daily activities: end-user perspective in designing a consumer mashups. iiWAS 2011: 222-229 - [c1]Zhenzhen Zhao, Ji Liu, Noël Crespi:
The design of activity-oriented social networking: Dig-Event. iiWAS 2011: 420-425
Coauthor Index
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