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ORCIDDi Wu 0056
Person information
- affiliation: Southwest University, College of Computer and Information Science, Chongqing, China
- affiliation (PhD 2019): Chinese Academy of Sciences, Chongqing Institute of Green and Intelligent Technology, China
Other persons with the same name
- Di Wu — disambiguation page
- Di Wu 0001
![[0000-0002-9433-7725]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0002-9433-7725")
— Sun Yat-Sen University, School of Data and Computer Science, Guangzhou, China (and 3 more) - Di Wu 0002 — Hunan University, Department of Computer Engineering, Changsha, China (and 2 more)
- Di Wu 0003 — Linköping University, Sweden
- Di Wu 0004 — Chinese Academy of Sciences, Institute of Information Engineering, Beijing, China (and 1 more)
- Di Wu 0005 — Huazhong University of Science and Technology, Wuhan, China
- Di Wu 0006 — MIT Media Lab, Cambridge, MA, USA (and 2 more)
- Di Wu 0007 — Dalian University of Technology, School of Computer Science and Technology, China
- Di Wu 0008 — The Chinese University of Hong Kong, Department of Systems Engineering and Engineering Management, Hong Kong
- Di Wu 0009 — PingAn Insurance Group Company of China Ltd., Shenzhen, China (and 2 more)
- Di Wu 0010 — Falcon Computing Solutions, Inc., Los Angeles, CA, USA (and 1 more)
- Di Wu 0011 — Jilin University, State Key Laboratory of Theoretical and Computational Chemistry, Changchun, China
- Di Wu 0012 — Zhejiang University, College of Biosystems Engineering and Food Science, Hangzhou, China
- Di Wu 0013 — Tsinghua University, Beijing, China
- Di Wu 0014 — Nanjing University, State Key Laboratory for Novel Software Technology, Nanjing, China
- Di Wu 0015 — Nanjing University of Aeronautics and Astronautics, Nanjing, China
- Di Wu 0016 — University of Wisconsin-Madison, Madison, WI, USA (and 1 more)
- Di Wu 0017 — Texas A&M University, College Station, TX, USA
- Di Wu 0018 — Central China Normal University, National Engineering Research Center for E-Learning, Wuhan, China
- Di Wu 0019 — Rutgers University, Winlab, Piscataway, NJ, USA
- Di Wu 0020 — Shanghai University of Engineering Science, Shanghai Collaborative Innovation Center of Laser Advanced Manufacturing Technology, Shanghai, China (and 1 more)
- Di Wu 0021 — Pacific Northwest National Laboratory, Richland, WA, USA
- Di Wu 0022 — CAS, Insitute of Computing Technology, Beijing, China (and 1 more)
- Di Wu 0023 — Beihang University, Robotics Institute, Beijing, China
- Di Wu 0024 — Chinese Academy of Sciences, Beijing Key Laboratory of Space Environment Exploration, Beijing, China
- Di Wu 0025 — Harbin Engineering University, College of Automation, China
- Di Wu 0026 — University of Oklahoma, School of Electrical and Computer Engineering, USA
- Di Wu 0027 — Shaanxi Normal University, Xi'an, China (and 2 more)
- Di Wu 0028 — Harbin Institute of Technology, School of Electronics and Information Engineering, China
- Di Wu 0029 — University of Melbourne, Australia
- Di Wu 0030 — Tongji University, School of Electronics and Information Engineering, Institute of Machine Learning and Systems Biology, Shanghai, China
- Di Wu 0031 — University of Edinburgh, Institute for Digital Communications, Edinburgh, UK
- Di Wu 0032 — Xi'an Jiaotong University, School of Managemen, Xi'an, China
- Di Wu 0033 — Hebei University of Engineering, Department of Information and Electronic Engineering, Handan, China (and 1 more)
- Di Wu 0034 — Georgia Institute of Technology, Atlanta, GA, USA
- Di Wu 0035 — Norwegian University of Science and Technology, Ålesund, Norway (and 2 more)
- Di Wu 0036 — Nankai University, Lianjin, China
- Di Wu 0037 — University of Southern California, Los Angeles, CA, USA
- Di Wu 0038 — Dalian University of Technology, School of Control Science and Engineering, Dalian, China (and 2 more)
- Di Wu 0039 — Dalian University of Technology, School of Software, Dalian, China
- Di Wu 0040 — Chinese Academy of Sciences, CAS Key Laboratory of FAST, National Astronomical Observatories, Beijing, China
- Di Wu 0041 — Harbin Engineering University, College of Computer Science and Technology, Harbin, China (and 1 more)
- Di Wu 0042 — New Jersey Institute of Technology, Advanced Networking Laboratory, Newark, NJ, USA
- Di Wu 0043 — Beihang University, School of Electronic and Information Engineering, Beijing, China
- Di Wu 0044 — McGill University, School of Computer Science, Montreal, Canada
- Di Wu 0045 — University of California at Los Angeles, Electrical Engineering Department, Los Angeles, CA, USA
- Di Wu 0046 — Hunan Institute of Engineering, College of Electrical and Information Engineering, Xiangtan, China
- Di Wu 0047 — Fourth Military Medical University, Department of Psychology, Shaanxi, China
- Di Wu 0048 — Hefei University of Technology, School of Electrical Engineering and Automation, Hefei, China
- Di Wu 0049 — Chinese Academy of Sciences, Changchun Institute of Optics, Fine Mechanics and Physics (CIOMP), Changchun, China
- Di Wu 0050 — University of Southern Queensland, Australia (and 2 more)
- Di Wu 0051 — University of Technology Sydney, School of Civil and Environmental Engineering, Sydney, Australia (and 1 more)
- Di Wu 0052 — Southeast University, School of Automation, Nanjing, China (and 1 more)
- Di Wu 0053 — Johns Hopkins University, Laboratory for Computational Sensing and Robotics, Baltimore, MD, USA (and 1 more)
- Di Wu 0054 — University of California, Los Angeles, CA, USA
- Di Wu 0055 — Hainan Century Frontier Asset Management Co. Ltd, China
- Di Wu 0057 — Westlake University, Institute of Advanced Technology, CenBRAIN Neurotech, AI Lab, Research Center for Industries of the Future, Hangzhou, China
- Di Wu 0058 — Hainan University, School of Information and Communication Engineering, Haikou, China (and 1 more)
- Di Wu 0059 — Northwestern Polytechnical University, Xi'an, Shaanxi, China (and 2 more)
- Di Wu 0060 — Shenzhen University, College of Electronics and Information Engineering, Guangdong, China (and 4 more)
- Di Wu 0061 — Horizon Robotics, Beijing, China (and 2 more)
- Di Wu 0062 — Xi'an Jiaotong University, School of Computer Science and Technology, Shaanxi, China
- Di Wu 0063 — Harbin Engineering University, Department of Intelligent Systems Science and Engineering, China
- Di Wu 0064 — Beijing University of Technology, Faculty of Information Technology, China
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2020 – today
- 2024
[j31]Song Deng, Qianliang Li, Renjie Dai, Siming Wei, Di Wu, Yi He, Xindong Wu:
A Chinese power text classification algorithm based on deep active learning. Appl. Soft Comput. 150: 111067 (2024)- [j30]Teng Huang, Cheng Liang, Di Wu, Yi He:
A Debiasing Autoencoder for Recommender System. IEEE Trans. Consumer Electron. 70(1): 3603-3613 (2024) - [j29]Di Wu, Xin Luo, Yi He, Mengchu Zhou:
A Prediction-Sampling-Based Multilayer-Structured Latent Factor Model for Accurate Representation to High-Dimensional and Sparse Data. IEEE Trans. Neural Networks Learn. Syst. 35(3): 3845-3858 (2024) - [j28]Xiaoyu Shi, Quanliang Liu, Hong Xie, Di Wu, Bo Peng, Mingsheng Shang, Defu Lian:
Relieving Popularity Bias in Interactive Recommendation: A Diversity-Novelty-Aware Reinforcement Learning Approach. ACM Trans. Inf. Syst. 42(2): 52:1-52:30 (2024) - [j27]Di Wu, Peng Zhang, Yi He, Xin Luo:
MMLF: Multi-Metric Latent Feature Analysis for High-Dimensional and Incomplete Data. IEEE Trans. Serv. Comput. 17(2): 575-588 (2024) - [c21]Di Wu, Wu Sun, Yi He, Zhong Chen, Xin Luo:
MKG-FENN: A Multimodal Knowledge Graph Fused End-to-End Neural Network for Accurate Drug-Drug Interaction Prediction. AAAI 2024: 10216-10224 - 2023
- [j26]Song Deng, Qicong Hu, Di Wu, Yi He:
BCTC-KSM: A blockchain-assisted threshold cryptography for key security management in power IoT data sharing. Comput. Electr. Eng. 108: 108666 (2023) - [j25]Jiangli Duan, Guoyin Wang, Xin Hu, Deyou Xia, Di Wu:
Mining multigranularity decision rules of concept cognition for knowledge graphs based on three-way decision. Inf. Process. Manag. 60(4): 103365 (2023) - [j24]Dianlong You, Shina Niu, Siqi Dong, Huigui Yan, Zhen Chen, Di Wu, Limin Shen, Xindong Wu:
Counterfactual explanation generation with minimal feature boundary. Inf. Sci. 625: 342-366 (2023) - [j23]Dianlong You, Siqi Dong, Shina Niu, Huigui Yan, Zhen Chen, Shunfu Jin, Di Wu, Xindong Wu:
Local causal structure learning for streaming features. Inf. Sci. 647: 119502 (2023) - [j22]Di Wu, Yi He, Xin Luo:
A Graph-Incorporated Latent Factor Analysis Model for High-Dimensional and Sparse Data. IEEE Trans. Emerg. Top. Comput. 11(4): 907-917 (2023) - [j21]Jia Chen, Renfang Wang, Di Wu, Xin Luo:
A Differential Evolution-Enhanced Position-Transitional Approach to Latent Factor Analysis. IEEE Trans. Emerg. Top. Comput. Intell. 7(2): 389-401 (2023) - [j20]Song Deng, Jiantang Zhang, Di Wu, Yi He, Xiangpeng Xie, Xindong Wu:
A Quantitative Risk Assessment Model for Distribution Cyber-Physical System Under Cyberattack. IEEE Trans. Ind. Informatics 19(3): 2899-2908 (2023) - [j19]Dianlong You, Jiawei Xiao, Yang Wang, Huigui Yan, Di Wu, Zhen Chen, Limin Shen, Xindong Wu:
Online Learning From Incomplete and Imbalanced Data Streams. IEEE Trans. Knowl. Data Eng. 35(10): 10650-10665 (2023) - [j18]Di Wu, Peng Zhang, Yi He, Xin Luo:
A Double-Space and Double-Norm Ensembled Latent Factor Model for Highly Accurate Web Service QoS Prediction. IEEE Trans. Serv. Comput. 16(2): 802-814 (2023) - [j17]Di Wu, Bo Sun, Mingsheng Shang:
Hyperparameter Learning for Deep Learning-Based Recommender Systems. IEEE Trans. Serv. Comput. 16(4): 2699-2712 (2023) - [j16]Song Deng, Yujia Zhai, Di Wu, Dong Yue, Xiong Fu, Yi He:
A Lightweight Dynamic Storage Algorithm With Adaptive Encoding for Energy Internet. IEEE Trans. Serv. Comput. 16(5): 3115-3128 (2023) - [c20]Di Wu, Shengda Zhuo, Yu Wang, Zhong Chen, Yi He:
Online Semi-supervised Learning with Mix-Typed Streaming Features. AAAI 2023: 4720-4728 - [c19]Cheng Liang, Di Wu, Yi He, Teng Huang, Zhong Chen, Xin Luo:
MMA: Multi-Metric-Autoencoder for Analyzing High-Dimensional and Incomplete Data. ECML/PKDD (5) 2023: 3-19 - [c18]Liping Zhang, Di Wu, Xin Luo:
An Error Correction Mid-term Electricity Load Forecasting Model Based on Seasonal Decomposition. SMC 2023: 2415-2420 - [c17]Ruiyang Xu, Di Wu, Xin Luo:
Online Sparse Streaming Feature Selection via Decision Risk. SMC 2023: 4190-4195 - [i7]Ruiyang Xu, Di Wu, Xin Luo:
Online Sparse Streaming Feature Selection Using Adapted Classification. CoRR abs/2302.14056 (2023) - [i6]Liping Zhang, Di Wu, Xin Luo:
An Error Correction Mid-term Electricity Load Forecasting Model Based on Seasonal Decomposition. CoRR abs/2306.10826 (2023) - 2022
- [j15]Song Deng, Fulin Chen, Di Wu, Yi He, Hui Ge, Yuan Ge:
Quantitative combination load forecasting model based on forecasting error optimization. Comput. Electr. Eng. 101: 108125 (2022) - [j14]Xiaoyu Xu, Di Wu, Mingsheng Shang:
A structure-characteristic-aware network embedding model via differential evolution. Expert Syst. Appl. 204: 117611 (2022) - [j13]Wenjun Li, Anli Yan, Di Wu, Taoyu Zhu, Teng Huang, Xuandi Luo, Shaowei Wang:
DPCL: Contrastive representation learning with differential privacy. Int. J. Intell. Syst. 37(11): 9701-9725 (2022) - [j12]Xiaoyu Xu, Guansong Pang, Di Wu, Mingsheng Shang:
Joint hyperbolic and Euclidean geometry contrastive graph neural networks. Inf. Sci. 609: 799-815 (2022) - [j11]Di Wu, Xin Luo, Mingsheng Shang, Yi He, Guoyin Wang, Xindong Wu:
A Data-Characteristic-Aware Latent Factor Model for Web Services QoS Prediction. IEEE Trans. Knowl. Data Eng. 34(6): 2525-2538 (2022) - [j10]Di Wu, Mingsheng Shang, Xin Luo, Zidong Wang:
An L1-and-L2-Norm-Oriented Latent Factor Model for Recommender Systems. IEEE Trans. Neural Networks Learn. Syst. 33(10): 5775-5788 (2022) - [j9]Di Wu, Qiang He, Xin Luo, Mingsheng Shang, Yi He, Guoyin Wang:
A Posterior-Neighborhood-Regularized Latent Factor Model for Highly Accurate Web Service QoS Prediction. IEEE Trans. Serv. Comput. 15(2): 793-805 (2022) - [j8]Di Wu, Yi He, Xin Luo, MengChu Zhou:
A Latent Factor Analysis-Based Approach to Online Sparse Streaming Feature Selection. IEEE Trans. Syst. Man Cybern. Syst. 52(11): 6744-6758 (2022) - [c16]Bo Sun, Di Wu, Mingsheng Shang, Yi He:
Toward Auto-Learning Hyperparameters for Deep Learning-Based Recommender Systems. DASFAA (2) 2022: 323-331 - [c15]Zhikai Yu, Di Wu, Yi He:
A Robust Latent Factor Analysis Model for Incomplete Data Recovery in Wireless Sensor Networks. EDGE 2022: 178-183 - [c14]Feilong Chen, Di Wu, Jie Yang, Yi He:
Online Sparse Streaming Feature Selection with Uncertainty. ICNSC 2022: 1-6 - [c13]Cheng Liang, Yi He, Teng Huang, Di Wu:
AutoRec++: Incorporating Debias Methods into Autoencoder-based Recommender System. SmartWorld/UIC/ScalCom/DigitalTwin/PriComp/Meta 2022: 1876-1881 - [c12]Yuanpeng Hu, Xianmin Wang, Cheng Liang, Jing Li, Di Wu, Yi He:
OR-AutoRec: An Outlier-Resilient Autoencoder-based Recommendation model. SmartWorld/UIC/ScalCom/DigitalTwin/PriComp/Meta 2022: 1918-1923 - [i5]Jia Chen, Di Wu, Xin Luo:
A Differential Evolution-Enhanced Latent Factor Analysis Model for High-dimensional and Sparse Data. CoRR abs/2204.00861 (2022) - [i4]Di Wu, Yi He, Xin Luo:
Graph-incorporated Latent Factor Analysis for High-dimensional and Sparse Matrices. CoRR abs/2204.07818 (2022) - [i3]Di Wu, Peng Zhang, Yi He, Xin Luo:
A Multi-Metric Latent Factor Model for Analyzing High-Dimensional and Sparse data. CoRR abs/2204.07819 (2022) - [i2]Feilong Chen, Di Wu, Jie Yang, Yi He:
An Online Sparse Streaming Feature Selection Algorithm. CoRR abs/2208.01562 (2022) - [i1]Cheng Liang, Teng Huang, Yi He, Song Deng, Di Wu, Xin Luo:
Multi-Metric AutoRec for High Dimensional and Sparse User Behavior Data Prediction. CoRR abs/2212.13879 (2022) - 2021
- [j7]Di Wu, Xin Luo:
Robust Latent Factor Analysis for Precise Representation of High-Dimensional and Sparse Data. IEEE CAA J. Autom. Sinica 8(4): 796-805 (2021) - [j6]Xin Luo, Mengchu Zhou, Shuai Li, Di Wu, Zhigang Liu, Mingsheng Shang:
Algorithms of Unconstrained Non-Negative Latent Factor Analysis for Recommender Systems. IEEE Trans. Big Data 7(1): 227-240 (2021) - [j5]Yi He, Baijun Wu, Di Wu, Ege Beyazit, Sheng Chen, Xindong Wu:
Toward Mining Capricious Data Streams: A Generative Approach. IEEE Trans. Neural Networks Learn. Syst. 32(3): 1228-1240 (2021) - [j4]Di Wu, Xin Luo, Mingsheng Shang, Yi He, Guoyin Wang, MengChu Zhou:
A Deep Latent Factor Model for High-Dimensional and Sparse Matrices in Recommender Systems. IEEE Trans. Syst. Man Cybern. Syst. 51(7): 4285-4296 (2021) - [c11]Peng Zhang, Yi He, Di Wu:
An Ensemble Latent Factor Model for Highly Accurate Web Service QoS Prediction. ICBK 2021: 361-368 - 2020
- [c10]Yi He, Baijun Wu, Di Wu, Xindong Wu:
On Partial Multi-Task Learning. ECAI 2020: 1174-1181 - [c9]Xin Luo, Ye Yuan, Di Wu:
Adaptive Regularization-Incorporated Latent Factor Analysis. ICKG 2020: 481-488 - [c8]Di Wu, Gang Lu, Zhicheng Xu:
Robust and Accurate Representation Learning for High-dimensional and Sparse Matrices in Recommender Systems. ICKG 2020: 489-496 - [c7]Di Wu, Long Jin, Xin Luo:
PMLF: Prediction-Sampling-based Multilayer-Structured Latent Factor Analysis. ICDM 2020: 671-680 - [c6]Ye Yuan, Xin Luo, Mingsheng Shang, Di Wu:
A Generalized and Fast-converging Non-negative Latent Factor Model for Predicting User Preferences in Recommender Systems. WWW 2020: 498-507
2010 – 2019
- 2019
- [c5]Di Wu, Yi He, Xin Luo, Mingsheng Shang, Xindong Wu:
Online Feature Selection with Capricious Streaming Features: A General Framework. IEEE BigData 2019: 683-688 - [c4]Yi He, Baijun Wu, Di Wu, Ege Beyazit, Sheng Chen, Xindong Wu:
Online Learning from Capricious Data Streams: A Generative Approach. IJCAI 2019: 2491-2497 - [c3]Di Wu, Xin Luo, Mingsheng Shang, Yi He, Guoyin Wang, Xindong Wu:
A Data-Aware Latent Factor Model for Web Service QoS Prediction. PAKDD (1) 2019: 384-399 - 2018
- [j3]Di Wu, Mingsheng Shang, Xin Luo, Ji Xu, Huyong Yan, Weihui Deng, Guoyin Wang:
Self-training semi-supervised classification based on density peaks of data. Neurocomputing 275: 180-191 (2018) - [j2]Di Wu, Xin Luo, Guoyin Wang, Mingsheng Shang, Ye Yuan, Huyong Yan:
A Highly Accurate Framework for Self-Labeled Semisupervised Classification in Industrial Applications. IEEE Trans. Ind. Informatics 14(3): 909-920 (2018) - [c2]Di Wu, Mingsheng Shang, Guoyin Wang, Li Li:
A self-training semi-supervised classification algorithm based on density peaks of data and differential evolution. ICNSC 2018: 1-6 - [c1]Yi He, Di Wu, Ege Beyazit, Xiaoduan Sun, Xindong Wu:
Supervised Data Synthesizing and Evolving - A Framework for Real-World Traffic Crash Severity Classification. ICTAI 2018: 163-170 - 2012
- [j1]Tao Zhu, Di Wu, Min Liu, De-Wen Duan:
In-Line Fiber Optic Interferometric Sensors in Single-Mode Fibers. Sensors 12(8): 10430-10449 (2012)
Coauthor Index
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