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ORCIDWenbin Zhang 0002
张雯斌
Person information
- unicode name: 张雯斌
- affiliation: Florida International University, Miami, FL, USA
- affiliation (former): Carnegie Mellon University, Pittsburgh, PA, USA
- affiliation (PhD): University of Maryland, Baltimore County, MD, USA
Other persons with the same name
- Wenbin Zhang (aka: WenBin Zhang, Wen-bin Zhang, Wen-Bin Zhang) — disambiguation page
- Wenbin Zhang 0001
![[0000-0003-2320-4412]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0003-2320-4412")
— Harbin Institute of Technology, Communication Research Center, China - Wenbin Zhang 0003 — IBM, Singapore (and 1 more)
- Wenbin Zhang 0004 — Shandong University, School of Computer Science and Technology, Jinan, China
- Wenbin Zhang 0005 — Epic Systems Corporation, Verona, WI, USA (and 1 more)
- Wenbin Zhang 0006 — Kunming University of Science and Technology, Faculty of Science, China
- Wenbin Zhang 0007 — State University of New York at Stony Brook, Department of Computer Science, NY, USA
- Wen-Bin Zhang 0008 (aka: Wenbin Zhang 0008) — Chinese University of Hong Kong, Institute of Future Cities, Hong Kong (and 2 more)
- Wenbin Zhang 0009 — Honghe University, Engineering College, Mengzi, China
- Wenbin Zhang 0010 — Tianjin University, Information and Network Center, China
- Wenbin Zhang 0011 — Zhejiang University, College of Control Science and Engineering, Hangzhou, China
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2020 – today
- 2025
[j25]Nripsuta Ani Saxena, Wenbin Zhang, Cyrus Shahabi:
Unveiling and mitigating bias in ride-hailing pricing for equitable policy making. AI Ethics 5(2): 1549-1560 (2025)- [j24]Zichong Wang, Zhibo Chu, Thang Viet Doan, Shiwen Ni, Min Yang, Wenbin Zhang:
History, development, and principles of large language models: an introductory survey. AI Ethics 5(3): 1955-1971 (2025) - [j23]Zichong Wang, Zhipeng Yin, Xingyu Zhang, Yuying Zhang, Xudong He, Shaowei Wang, Houbing Song, Liping Yang, Wenbin Zhang:
Towards fair graph-based machine learning software: unveiling and mitigating graph model bias. AI Ethics 5(6): 6279-6296 (2025) - [j22]Wenbin Zhang, Shuigeng Zhou, Toby Walsh, Jeremy C. Weiss:
Fairness amidst non-IID graph data: A literature review. AI Mag. 46(1) (2025) - [j21]Conghao Yan, Qingzhao Kong, Wenbin Zhang:
The neighborhood rough set based on division-mining-fusion strategy. Appl. Soft Comput. 184: 113749 (2025) - [j20]Zhen Liu, Ruoyu Wang, Bitao Peng, Lingyu Qiu, Qingqing Gan, Changji Wang, Wenbin Zhang:
LDCDroid: Learning data drift characteristics for handling the model aging problem in Android malware detection. Comput. Secur. 150: 104294 (2025) - [j19]Shamim Yazdani, Akansha Singh, Nripsuta Saxena, Zichong Wang, Avash Palikhe, Deng Pan, Umapada Pal, Jie Yang, Wenbin Zhang:
Generative AI in depth: A survey of recent advances, model variants, and real-world applications. J. Big Data 12(1): 230 (2025) - [j18]Wenbin Zhang:
Online and Customizable Fairness-aware Learning. Knowl. Inf. Syst. 67(12): 11549-11576 (2025) - [j17]Josh Jia-Ching Ying, Chia-Chen Liu, Vincent S. Tseng, Wenbin Zhang, Ji Zhang:
Forecasting leading economic indicators in the US from financial news using multi-task learning. Soft Comput. 29(7): 3641-3657 (2025) - [j16]Jun Liu, Zhenglun Kong, Pu Zhao, Weihao Zeng, Hao Tang, Xuan Shen, Changdi Yang, Wenbin Zhang, Geng Yuan, Wei Niu, Xue Lin, Yanzhi Wang:
TSLA: A Task-Specific Learning Adaptation for Semantic Segmentation on Autonomous Vehicles Platform. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 44(4): 1406-1419 (2025) - [j15]Azmain Kabir, Shaowei Wang, Yuan Tian, Tse-Hsun (Peter) Chen, Muhammad Asaduzzaman, Wenbin Zhang:
ZS4C: Zero-Shot Synthesis of Compilable Code for Incomplete Code Snippets Using LLMs. ACM Trans. Softw. Eng. Methodol. 34(4): 90:1-90:30 (2025) - [c74]Jun Liu, Zhenglun Kong, Pu Zhao, Changdi Yang, Xuan Shen, Hao Tang, Geng Yuan, Wei Niu, Wenbin Zhang, Xue Lin, Dong Huang, Yanzhi Wang:
Toward Adaptive Large Language Models Structured Pruning via Hybrid-grained Weight Importance Assessment. AAAI 2025: 18879-18887 - [c73]Zichong Wang, Zhibo Chu, Thang Viet Doan, Shaowei Wang, Yongkai Wu, Vasile Palade, Wenbin Zhang:
Fair Graph U-Net: A Fair Graph Learning Framework Integrating Group and Individual Awareness. AAAI 2025: 28485-28493 - [c72]Zichong Wang, Nhat Hoang, Xingyu Zhang, Kevin Bello, Xiangliang Zhang, Sundararaja Sitharama Iyengar, Wenbin Zhang:
Towards Fair Graph Learning without Demographic Information. AISTATS 2025: 2107-2115 - [c71]Zichong Wang, Avash Palikhe, Zhipeng Yin, Wenbin Zhang:
Fairness in Language Models: A Tutorial. CIKM 2025: 6849-6852 - [c70]Zhipeng Yin, Zichong Wang, Avash Palikhe, Wenbin Zhang:
Uncertain Boundaries: A Tutorial on Copyright Challenges and Cross-Disciplinary Solutions for Generative AI. CIKM 2025: 6853-6856 - [c69]Jun Liu, Zhenglun Kong, Peiyan Dong, Xuan Shen, Pu Zhao, Hao Tang, Geng Yuan, Wei Niu, Wenbin Zhang, Xue Lin, Dong Huang, Yanzhi Wang:
RoRA: Efficient Fine-Tuning of LLM with Reliability Optimization for Rank Adaptation. ICASSP 2025: 1-5 - [c68]Zichong Wang, Wenbin Zhang:
FDGen: A Fairness-Aware Graph Generation Model. ICML 2025 - [c67]Mingyang Wu, Li Lin, Wenbin Zhang, Xin Wang, Zhenhuan Yang, Shu Hu:
Preserving AUC Fairness in Learning with Noisy Protected Groups. ICML 2025 - [c66]Zichong Wang, Fang Liu, Shimei Pan, Jun Liu, Fahad Saeed, Meikang Qiu, Wenbin Zhang:
fairGNN-WOD: Fair Graph Learning Without Complete Demographics. IJCAI 2025: 556-564 - [c65]Zichong Wang, Anqi Wu, Nuno Moniz, Shu Hu, Bart P. Knijnenburg, Xingquan Zhu, Wenbin Zhang:
Towards Fairness with Limited Demographics via Disentangled Learning. IJCAI 2025: 565-573 - [c64]Zichong Wang, Zhipeng Yin, Zhen Liu, Roland H. C. Yap, Xiaocai Zhang, Shu Hu, Wenbin Zhang:
Redefining Fairness: A Multi-dimensional Perspective and Integrated Evaluation Framework. ECML/PKDD (1) 2025: 336-353 - [c63]Zichong Wang, Zhipeng Yin, Liping Yang, Jun Zhuang, Rui Yu, Qingzhao Kong, Wenbin Zhang:
Fairness-Aware Graph Representation Learning with Limited Demographic Information. ECML/PKDD (1) 2025: 354-371 - [c62]Jintao Qu, Zichong Wang, Chenhao Wu, Wenbin Zhang, Dongmei Li:
Bridging Neural Networks and Dynamic Time Warping for Adaptive Time Series Classification. ECML/PKDD (7) 2025: 526-542 - [c61]Zhong Chen, Yi He, Di Wu, Wenbin Zhang, Zhiqiang Deng:
ℓ1, ∞ Mixed Norm Promoted Row Sparsity for Fast Online CUR Decomposition Learning in Varying Feature Spaces. SDM 2025: 124-133 - [i50]Jun Liu, Zhenglun Kong, Peiyan Dong, Changdi Yang, Xuan Shen, Pu Zhao, Hao Tang, Geng Yuan, Wei Niu, Wenbin Zhang, Xue Lin, Dong Huang, Yanzhi Wang:
RoRA: Efficient Fine-Tuning of LLM with Reliability Optimization for Rank Adaptation. CoRR abs/2501.04315 (2025) - [i49]Zhipeng Yin, Zichong Wang, Weifeng Xu, Jun Zhuang, Pallab Mozumder, Antoinette Smith, Wenbin Zhang:
Digital Forensics in the Age of Large Language Models. CoRR abs/2504.02963 (2025) - [i48]Jun Liu, Zhenglun Kong, Peiyan Dong, Changdi Yang, Tianqi Li, Hao Tang, Geng Yuan, Wei Niu, Wenbin Zhang, Pu Zhao, Xue Lin, Dong Huang, Yanzhi Wang:
Structured Agent Distillation for Large Language Model. CoRR abs/2505.13820 (2025) - [i47]Mingyang Wu, Li Lin, Wenbin Zhang, Xin Wang, Zhenhuan Yang, Shu Hu:
Preserving AUC Fairness in Learning with Noisy Protected Groups. CoRR abs/2505.18532 (2025) - [i46]Jun Zhuang, Hai Jin, Ye Zhang, Zhengjian Kang, Wenbin Zhang, Gaby G. Dagher, Haohan Wang:
Exploring the Vulnerability of the Content Moderation Guardrail in Large Language Models via Intent Manipulation. CoRR abs/2505.18556 (2025) - [i45]Avash Palikhe, Zhenyu Yu, Zichong Wang, Wenbin Zhang:
Towards Transparent AI: A Survey on Explainable Large Language Models. CoRR abs/2506.21812 (2025) - [i44]Jiale Zhang, Zichong Wang, Avash Palikhe, Zhipeng Yin, Wenbin Zhang:
Datasets for Fairness in Language Models: An In-Depth Survey. CoRR abs/2506.23411 (2025) - [i43]Jintao Qu, Zichong Wang, Chenhao Wu, Wenbin Zhang:
Bridging Neural Networks and Dynamic Time Warping for Adaptive Time Series Classification. CoRR abs/2507.09826 (2025) - [i42]Jun Liu, Zhenglun Kong, Changdi Yang, Fan Yang, Tianqi Li, Peiyan Dong, Joannah Nanjekye, Hao Tang, Geng Yuan, Wei Niu, Wenbin Zhang, Pu Zhao, Xue Lin, Dong Huang, Yanzhi Wang:
RCR-Router: Efficient Role-Aware Context Routing for Multi-Agent LLM Systems with Structured Memory. CoRR abs/2508.04903 (2025) - [i41]Jun Liu, Zhenglun Kong, Pu Zhao, Weihao Zeng, Hao Tang, Xuan Shen, Changdi Yang, Wenbin Zhang, Geng Yuan, Wei Niu, Xue Lin, Yanzhi Wang:
TSLA: A Task-Specific Learning Adaptation for Semantic Segmentation on Autonomous Vehicles Platform. CoRR abs/2508.12279 (2025) - [i40]Zhipeng Yin, Zichong Wang, Avash Palikhe, Zhen Liu, Jun Liu, Wenbin Zhang:
AMCR: A Framework for Assessing and Mitigating Copyright Risks in Generative Models. CoRR abs/2509.00641 (2025) - [i39]Gang Cheng, Hai Jin, Wenbin Zhang, Haohan Wang, Jun Zhuang:
Uncovering the Vulnerability of Large Language Models in the Financial Domain via Risk Concealment. CoRR abs/2509.10546 (2025) - [i38]Avash Palikhe, Zichong Wang, Zhipeng Yin, Rui Guo, Qiang Duan, Jie Yang, Wenbin Zhang:
Towards Transparent AI: A Survey on Explainable Language Models. CoRR abs/2509.21631 (2025) - [i37]Shamim Yazdani, Akansha Singh, Nripsuta Saxena, Zichong Wang, Avash Palikhe, Deng Pan, Umapada Pal, Jie Yang, Wenbin Zhang:
Generative AI in Depth: A Survey of Recent Advances, Model Variants, and Real-World Applications. CoRR abs/2510.21887 (2025) - 2024
- [j14]Wenbin Zhang:
AI fairness in practice: Paradigm, challenges, and prospects. AI Mag. 45(3): 386-395 (2024) - [j13]Feng Lin, Dongmei Li, Wenbin Zhang, Dongsheng Shi, Yuanzhou Jiao, Qianzhong Chen, Yiying Lin, Wentao Zhu:
Multi-modal knowledge graph inference via media convergence and logic rule. CAAI Trans. Intell. Technol. 9(1): 211-221 (2024) - [j12]Qingzhao Kong, Wanting Wang, Dongxiao Zhang, Wenbin Zhang:
Two kinds of average approximation accuracy. CAAI Trans. Intell. Technol. 9(2): 481-490 (2024) - [j11]Zhen Liu, Ruoyu Wang, Nathalie Japkowicz, Heitor Murilo Gomes, Bitao Peng, Wenbin Zhang:
SeGDroid: An Android malware detection method based on sensitive function call graph learning. Expert Syst. Appl. 235: 121125 (2024) - [j10]Zichong Wang, Meikang Qiu, Min Chen, Malek Ben Salem, Xin Yao, Wenbin Zhang:
Toward fair graph neural networks via real counterfactual samples. Knowl. Inf. Syst. 66(11): 6617-6641 (2024) - [j9]Xingyu Zhang, Yanshan Wang, Yun Jiang, Charissa B. Pacella, Wenbin Zhang:
Integrating structured and unstructured data for predicting emergency severity: an association and predictive study using transformer-based natural language processing models. BMC Medical Informatics Decis. Mak. 24(1): 372 (2024) - [j8]Zhibo Chu, Zichong Wang, Wenbin Zhang:
Fairness in Large Language Models: A Taxonomic Survey. SIGKDD Explor. 26(1): 34-48 (2024) - [j7]Zichong Wang, Zhipeng Yin, Yuying Zhang, Liping Yang, Tingting Zhang, Niki Pissinou, Yu Cai, Shu Hu, Yun Li, Liang Zhao, Wenbin Zhang:
Graph Fairness via Authentic Counterfactuals: Tackling Structural and Causal Challenges. SIGKDD Explor. 26(2): 89-98 (2024) - [j6]Zichong Wang, Zhipeng Yin, Yuying Zhang, Liping Yang, Tingting Zhang, Niki Pissinou, Yu Cai, Shu Hu, Yun Li, Liang Zhao, Wenbin Zhang:
FG-SMOTE: Towards Fair Node Classification with Graph Neural Network. SIGKDD Explor. 26(2): 99-108 (2024) - [c60]Wenbin Zhang:
Fairness with Censorship: Bridging the Gap between Fairness Research and Real-World Deployment. AAAI 2024: 22685 - [c59]Youpeng Li, Xinda Wang, Fuxun Yu, Lichao Sun, Wenbin Zhang, Xuyu Wang:
FedCAP: Robust Federated Learning via Customized Aggregation and Personalization. ACSAC 2024: 747-760 - [c58]Zhong Chen, Yi He, Di Wu, Liudong Zuo, Keren Li, Wenbin Zhang, Zhiqiang Deng:
ℓ1, 2-Norm and CUR Decomposition based Sparse Online Active Learning for Data Streams with Streaming Features. IEEE Big Data 2024: 384-393 - [c57]Thang Viet Doan, Zichong Wang, Nhat Nguyen Minh Hoang, Wenbin Zhang:
Fairness in Large Language Models in Three Hours. CIKM 2024: 5514-5517 - [c56]Eric Xu, Wenbin Zhang, Weifeng Xu:
Transforming Digital Forensics with Large Language Models: Unlocking Automation, Insights, and Justice. CIKM 2024: 5543-5546 - [c55]Hongpeng Jin, Maryam Akhavan Aghdam, Sai Nath Chowdary Medikonduru, Wenqi Wei, Xuyu Wang, Wenbin Zhang, Yanzhao Wu:
Effective Diversity Optimizations for High Accuracy Deep Ensembles. CogMI 2024: 278-287 - [c54]Nawrin Tabassum, Ka-Ho Chow, Xuyu Wang, Wenbin Zhang, Yanzhao Wu:
On the Efficiency of Privacy Attacks in Federated Learning. CVPR Workshops 2024: 4226-4235 - [c53]Zichong Wang, Wenbin Zhang:
Group Fairness with Individual and Censorship Constraints. ECAI 2024: 906-913 - [c52]Zichong Wang, David Ulloa, Tongjia Yu, Raju Rangaswami, Roland H. C. Yap, Wenbin Zhang:
Individual Fairness with Group Constraints in Graph Neural Networks. ECAI 2024: 1704-1711 - [c51]Zhipeng Yin, Sameeksha Agarwal, Ayesha Kashif, Matthew Gonzalez, Zichong Wang, Suqing Liu, Zhen Liu, Yanzhao Wu, Ian Stockwell, Weifeng Xu, Puqing Jiang, Xingyu Zhang, Wenbin Zhang:
Accessible Health Screening Using Body Fat Estimation by Image Segmentation. ICDM (Workshops) 2024: 405-414 - [c50]Zhipeng Yin, Zichong Wang, Wenbin Zhang:
Improving Fairness in Machine Learning Software via Counterfactual Fairness Thinking. ICSE Companion 2024: 420-421 - [c49]Saket S. Chaturvedi, Lan Zhang, Wenbin Zhang, Pan He, Xiaoyong Yuan:
BadFusion: 2D-Oriented Backdoor Attacks against 3D Object Detection. IJCAI 2024: 349-357 - [c48]Tianya Zhao, Ningning Wang, Yanzhao Wu, Wenbin Zhang, Xuyu Wang:
Backdoor Attacks Against Low-Earth Orbit Satellite Fingerprinting. INFOCOM (Workshops) 2024: 1-6 - [c47]Zichong Wang, Zhibo Chu, Ronald Blanco, Zhong Chen, Shu-Ching Chen, Wenbin Zhang:
Advancing Graph Counterfactual Fairness Through Fair Representation Learning. ECML/PKDD (7) 2024: 40-58 - [c46]Zichong Wang, Jocelyn Dzuong, Xiaoyong Yuan, Zhong Chen, Yanzhao Wu, Xin Yao, Wenbin Zhang:
Individual Fairness with Group Awareness Under Uncertainty. ECML/PKDD (5) 2024: 89-106 - [c45]Daniel Addai, Sarfraz Shaikh, Eric Xu, Wenbin Zhang, Weifeng Xu:
A Graph-Based Approach for Discovering Evidence Relationships Across Multiple Devices in Group Crimes. QRS Companion 2024: 1312-1313 - [i36]Azmain Kabir, Shaowei Wang, Yuan Tian, Tse-Hsun Chen, Muhammad Asaduzzaman, Wenbin Zhang:
ZS4C: Zero-Shot Synthesis of Compilable Code for Incomplete Code Snippets using ChatGPT. CoRR abs/2401.14279 (2024) - [i35]Zhibo Chu, Shiwen Ni, Zichong Wang, Xi Feng, Chengming Li, Xiping Hu, Ruifeng Xu, Min Yang, Wenbin Zhang:
History, Development, and Principles of Large Language Models-An Introductory Survey. CoRR abs/2402.06853 (2024) - [i34]Nripsuta Ani Saxena, Wenbin Zhang, Cyrus Shahabi:
Spatial Fairness: The Case for its Importance, Limitations of Existing Work, and Guidelines for Future Research. CoRR abs/2403.14040 (2024) - [i33]Zhibo Chu, Zichong Wang, Wenbin Zhang:
Fairness in Large Language Models: A Taxonomic Survey. CoRR abs/2404.01349 (2024) - [i32]Jocelyn Dzuong, Zichong Wang, Wenbin Zhang:
Uncertain Boundaries: Multidisciplinary Approaches to Copyright Issues in Generative AI. CoRR abs/2404.08221 (2024) - [i31]Nawrin Tabassum, Ka-Ho Chow, Xuyu Wang, Wenbin Zhang, Yanzhao Wu:
On the Efficiency of Privacy Attacks in Federated Learning. CoRR abs/2404.09430 (2024) - [i30]Saket S. Chaturvedi, Lan Zhang, Wenbin Zhang, Pan He, Xiaoyong Yuan:
BadFusion: 2D-Oriented Backdoor Attacks against 3D Object Detection. CoRR abs/2405.03884 (2024) - [i29]Thang Viet Doan, Zhibo Chu, Zichong Wang, Wenbin Zhang:
Fairness Definitions in Language Models Explained. CoRR abs/2407.18454 (2024) - [i28]Sribala Vidyadhari Chinta, Zichong Wang, Zhipeng Yin, Nhat Hoang, Matthew Gonzalez, Tai Le Quy, Wenbin Zhang:
FairAIED: Navigating Fairness, Bias, and Ethics in Educational AI Applications. CoRR abs/2407.18745 (2024) - [i27]Sribala Vidyadhari Chinta, Zichong Wang, Xingyu Zhang, Thang Doan Viet, Ayesha Kashif, Monique Antoinette Smith, Wenbin Zhang:
AI-Driven Healthcare: A Survey on Ensuring Fairness and Mitigating Bias. CoRR abs/2407.19655 (2024) - [i26]Thang Doan Viet, Zichong Wang, Minh Nhat Nguyen, Wenbin Zhang:
Fairness in Large Language Models in Three Hours. CoRR abs/2408.00992 (2024) - [i25]Jun Liu, Geng Yuan, Weihao Zeng, Hao Tang, Wenbin Zhang, Xue Lin, Xiaolin Xu, Dong Huang, Yanzhi Wang:
Brain Tumor Classification on MRI in Light of Molecular Markers. CoRR abs/2409.19583 (2024) - [i24]Youpeng Li, Xinda Wang, Fuxun Yu, Lichao Sun, Wenbin Zhang, Xuyu Wang:
FedCAP: Robust Federated Learning via Customized Aggregation and Personalization. CoRR abs/2410.13083 (2024) - 2023
- [j5]Wenbin Zhang, Jeremy C. Weiss:
Fairness with censorship and group constraints. Knowl. Inf. Syst. 65(6): 2571-2594 (2023) - [j4]Mohammad Ariful Islam, Hisham Siddique, Wenbin Zhang, Israat Haque:
A Deep Neural Network-Based Communication Failure Prediction Scheme in 5G RAN. IEEE Trans. Netw. Serv. Manag. 20(2): 1140-1152 (2023) - [c44]Wenbin Zhang, Tina Hernandez-Boussard, Jeremy C. Weiss:
Censored Fairness through Awareness. AAAI 2023: 14611-14619 - [c43]Jun Liu, Chao Wu, Geng Yuan, Wei Niu, Wenbin Zhang, Houbing Herbert Song:
A Scalable Real-time Semantic Segmentation Network for Autonomous Driving. AMC-SME 2023: 3-12 - [c42]Xin Huang, Chenxi Wang, Wenbin Zhang, Sanjay Purushotham, Jianwu Wang:
DRLO: Deep Representation Learning for Large Scale Off-track Satellite Remote Sensing Data. IEEE Big Data 2023: 1410-1418 - [c41]Hongpeng Jin, Wenqi Wei, Xuyu Wang, Wenbin Zhang, Yanzhao Wu:
Rethinking Learning Rate Tuning in the Era of Large Language Models. CogMI 2023: 112-121 - [c40]Xin Huang, Xiangyang Meng, Ni Zhao, Wenbin Zhang, Jianwu Wang:
Fair-DSP: Fair Dynamic Survival Prediction on Longitudinal Electronic Health Record. DaWaK 2023: 149-157 - [c39]Wenbin Zhang, Zichong Wang, Juyong Kim, Cheng Cheng, Thomas Oommen, Pradeep Ravikumar, Jeremy C. Weiss:
Individual Fairness Under Uncertainty. ECAI 2023: 3042-3049 - [c38]Zichong Wang, Nripsuta Saxena, Tongjia Yu, Sneha Karki, Tyler Zetty, Israat Haque, Shan Zhou, Dukka Kc, Ian Stockwell, Xuyu Wang, Albert Bifet, Wenbin Zhang:
Preventing Discriminatory Decision-making in Evolving Data Streams. FAccT 2023: 149-159 - [c37]Zichong Wang, Giri Narasimhan, Xin Yao, Wenbin Zhang:
Mitigating Multisource Biases in Graph Neural Networks via Real Counterfactual Samples. ICDM 2023: 638-647 - [c36]Yu Cai, Drew Youngstrom, Wenbin Zhang:
Exploring Approaches for Teaching Cybersecurity and AI for K-12. ICDM (Workshops) 2023: 1559-1564 - [c35]Sribala Vidyadhari Chinta, Karen Fernandes, Ningxi Cheng, Jordan Fernandez, Shamim Yazdani, Zhipeng Yin, Zichong Wang, Xuyu Wang, Weifeng Xu, Jun Liu, Chong Siang Yew, Puqing Jiang, Wenbin Zhang:
Optimization and Improvement of Fake News Detection using Voting Technique for Societal Benefit. ICDM (Workshops) 2023: 1565-1574 - [c34]Zichong Wang, Charles Wallace, Albert Bifet, Xin Yao, Wenbin Zhang:
FG2AN: Fairness-Aware Graph Generative Adversarial Networks. ECML/PKDD (2) 2023: 259-275 - [c33]Nripsuta Ani Saxena, Wenbin Zhang, Cyrus Shahabi:
Missed Opportunities in Fair AI. SDM 2023: 961-964 - [i23]Nripsuta Ani Saxena, Wenbin Zhang, Cyrus Shahabi:
Unveiling and Mitigating Bias in Ride-Hailing Pricing for Equitable Policy Making. CoRR abs/2301.03489 (2023) - [i22]Wenbin Zhang, Jeremy C. Weiss:
Fair Decision-making Under Uncertainty. CoRR abs/2301.12364 (2023) - [i21]Wenbin Zhang, Juyong Kim, Zichong Wang, Pradeep Ravikumar, Jeremy C. Weiss:
Individual Fairness Guarantee in Learning with Censorship. CoRR abs/2302.08015 (2023) - [i20]Zichong Wang, Nripsuta Saxena, Tongjia Yu, Sneha Karki, Tyler Zetty, Israat Haque, Shan Zhou, Dukka Kc, Ian Stockwell, Albert Bifet, Wenbin Zhang:
Preventing Discriminatory Decision-making in Evolving Data Streams. CoRR abs/2302.08017 (2023) - [i19]Zichong Wang, Yang Zhou, Meikang Qiu, Israat Haque, Laura Brown, Yi He, Jianwu Wang, David Lo, Wenbin Zhang:
Towards Fair Machine Learning Software: Understanding and Addressing Model Bias Through Counterfactual Thinking. CoRR abs/2302.08018 (2023) - [i18]Hongpeng Jin, Wenqi Wei, Xuyu Wang, Wenbin Zhang, Yanzhao Wu:
Rethinking Learning Rate Tuning in the Era of Large Language Models. CoRR abs/2309.08859 (2023) - [i17]Xuejiao Tang, Jiong Qiu, Wenbin Zhang, Ibrahim Toure, Mingli Zhang, Enza Messina, Xueping Xie, Xuebing Wang, Sheng Yu:
The Internet of Responsibilities-Connecting Human Responsibilities using Big Data and Blockchain. CoRR abs/2312.04729 (2023) - 2022
- [j3]Zhen Liu, Ruoyu Wang, Wenbin Zhang:
Improving the generalization of unsupervised feature learning by using data from different sources on gene expression data for cancer diagnosis. Medical Biol. Eng. Comput. 60(4): 1055-1073 (2022) - [j2]Tai Le Quy, Arjun Roy, Vasileios Iosifidis, Wenbin Zhang, Eirini Ntoutsi:
A survey on datasets for fairness-aware machine learning. WIREs Data Mining Knowl. Discov. 12(3) (2022) - [c32]Wenbin Zhang, Jeremy C. Weiss:
Longitudinal Fairness with Censorship. AAAI 2022: 12235-12243 - [c31]Thomas Guyet, Wenbin Zhang, Albert Bifet:
Incremental Mining of Frequent Serial Episodes Considering Multiple Occurrences. ICCS (1) 2022: 460-472 - [c30]Zhen Liu, Ruoyu Wang, Jin Yang, Wenbin Zhang:
Research on fine-tuning CNN for cancer diagnosis with gene expression data. ICMLC 2022: 140-145 - [i16]Thomas Guyet, Wenbin Zhang, Albert Bifet:
Incremental Mining of Frequent Serial Episodes Considering Multiple Occurrence. CoRR abs/2201.11650 (2022) - [i15]Wenbin Zhang, Jeremy C. Weiss, Shuigeng Zhou, Toby Walsh:
Fairness Amidst Non-IID Graph Data: A Literature Review. CoRR abs/2202.07170 (2022) - [i14]Wenbin Zhang, Jeremy C. Weiss:
Longitudinal Fairness with Censorship. CoRR abs/2203.16024 (2022) - [i13]Xuejiao Tang, Tai Le Quy, Eirini Ntoutsi, Kea Turner, Vasile Palade, Israat Haque, Peng Xu, Chris Brown, Wenbin Zhang:
Attention Mechanism based Cognition-level Scene Understanding. CoRR abs/2204.08027 (2022) - 2021
- [j1]Zhen Liu, Ruoyu Wang, Nathalie Japkowicz, Deyu Tang, Wenbin Zhang, Jie Zhao:
Research on unsupervised feature learning for Android malware detection based on Restricted Boltzmann Machines. Future Gener. Comput. Syst. 120: 91-108 (2021) - [c29]Xin Huang, Wenbin Zhang, Xuejiao Tang, Mingli Zhang, Jayachander Surbiryala, Vasileios Iosifidis, Zhen Liu, Ji Zhang:
LSTM Based Sentiment Analysis for Cryptocurrency Prediction. DASFAA (3) 2021: 617-621 - [c28]Xuejiao Tang, Xin Huang, Wenbin Zhang, Travers B. Child, Qiong Hu, Zhen Liu, Ji Zhang:
Cognitive Visual Commonsense Reasoning Using Dynamic Working Memory. DaWaK 2021: 81-93 - [c27]Mingli Zhang, Fan Zhang, Jianxin Zhang, Ahmad Chaddad, Fenghua Guo, Wenbin Zhang, Ji Zhang, Alan C. Evans:
AutoEncoder for Neuroimage. DEXA (2) 2021: 84-90 - [c26]Qiqiang Xu, Ji Zhang, Ting Yu, Wenbin Zhang, Mingli Zhang, Yonglong Luo, Fulong Chen, Zhen Liu:
An Effective Algorithm for Classification of Text with Weak Sequential Relationships. DEXA (2) 2021: 283-294 - [c25]Xuejiao Tang, Wenbin Zhang, Yi Yu, Kea Turner, Tyler Derr, Mengyu Wang, Eirini Ntoutsi:
Interpretable Visual Understanding with Cognitive Attention Network. ICANN (1) 2021: 555-568 - [c24]Wenbin Zhang, Jeremy C. Weiss:
Fair Decision-making Under Uncertainty. ICDM 2021: 886-895 - [c23]Zhen Liu, Ruoyu Wang, Wenbin Zhang, Deyu Tang:
An Unsupervised Feature Learning Method for Enhancing the Generalization of Cancer Diagnosis. ICMLC 2021: 252-257 - [c22]Xin Huang, Xuejiao Tang, Wenbin Zhang, Ji Zhang, Mingli Zhang, Wensheng Gan, Shichao Pei, Zhen Liu, Yiyi Huang:
A Generic Knowledge Based Medical Diagnosis Expert System. iiWAS 2021: 462-466 - [c21]Wenbin Zhang, Albert Bifet, Xiangliang Zhang, Jeremy C. Weiss, Wolfgang Nejdl:
FARF: A Fair and Adaptive Random Forests Classifier. PAKDD (2) 2021: 245-256 - [c20]Wenbin Zhang, Liming Zhang, Dieter Pfoser, Liang Zhao:
Disentangled Dynamic Graph Deep Generation. SDM 2021: 738-746 - [c19]Xuejian Wang, Wenbin Zhang, Aishwarya Jadhav, Jeremy C. Weiss:
Harmonic-Mean Cox Models: A Ruler for Equal Attention to Risk. SPACA 2021: 171-183 - [i12]Xin Huang, Wenbin Zhang, Yiyi Huang, Xuejiao Tang, Mingli Zhang, Jayachander Surbiryala, Vasileios Iosifidis, Zhen Liu, Ji Zhang:
LSTM Based Sentiment Analysis for Cryptocurrency Prediction. CoRR abs/2103.14804 (2021) - [i11]Xuejiao Tang, Xin Huang, Wenbin Zhang, Travers B. Child, Qiong Hu, Zhen Liu, Ji Zhang:
Cognitive Visual Commonsense Reasoning Using Dynamic Working Memory. CoRR abs/2107.01671 (2021) - [i10]Xuejiao Tang, Wenbin Zhang, Yi Yu, Kea Turner, Tyler Derr, Mengyu Wang, Eirini Ntoutsi:
Interpretable Visual Understanding with Cognitive Attention Network. CoRR abs/2108.02924 (2021) - [i9]Vasileios Iosifidis, Wenbin Zhang, Eirini Ntoutsi:
Online Fairness-Aware Learning with Imbalanced Data Streams. CoRR abs/2108.06231 (2021) - [i8]Wenbin Zhang, Albert Bifet, Xiangliang Zhang, Jeremy C. Weiss, Wolfgang Nejdl:
FARF: A Fair and Adaptive Random Forests Classifier. CoRR abs/2108.07403 (2021) - [i7]Xin Huang, Xuejiao Tang, Wenbin Zhang, Shichao Pei, Ji Zhang, Wensheng Gan, Mingli Zhang, Zhen Liu, Ruijun Chen, Yiyi Huang:
A Generic Knowledge Based Medical Diagnosis Expert System. CoRR abs/2110.04439 (2021) - 2020
- [c18]Xuejiao Tang, Liuhua Zhang, Wenbin Zhang, Xin Huang, Vasileios Iosifidis, Zhen Liu, Mingli Zhang, Enza Messina, Ji Zhang:
Using Machine Learning to Automate Mammogram Images Analysis. BIBM 2020: 757-764 - [c17]Srinivas Danda, Ji Zhang, Xiaohui Tao, Jerry Chun-Wei Lin, Wenbin Zhang:
Context-aware Adaptive Outlier Detection in Trajectory Data. IEEE BigData 2020: 5655-5657 - [c16]Xuejiao Tang, Jiong Qiu, Ruijun Chen, Wenbin Zhang, Vasileios Iosifidis, Zhen Liu, Wei Meng, Mingli Zhang, Ji Zhang:
A Data-driven Human Responsibility Management System. IEEE BigData 2020: 5834-5838 - [c15]Mingli Zhang, Xin Zhao, Wenbin Zhang, Ahmad Chaddad, Alan C. Evans, Jean-Baptiste Poline:
Deep Discriminative Learning for Autism Spectrum Disorder Classification. DEXA (1) 2020: 435-443 - [c14]Wenbin Zhang, Albert Bifet:
FEAT: A Fairness-Enhancing and Concept-Adapting Decision Tree Classifier. DS 2020: 175-189 - [c13]Divya Sukumar, Ji Zhang, Xiaohui Tao, Xin Wang, Wenbin Zhang:
Predicting Workplace Injuries Using Machine Learning Algorithms. DSAA 2020: 763-764 - [c12]Liming Zhang, Wenbin Zhang, Nathalie Japkowicz:
Conditional-UNet: A Condition-aware Deep Model for Coherent Human Activity Recognition From Wearables. ICPR 2020: 5889-5896 - [c11]Wenbin Zhang, Mingli Zhang, Ji Zhang, Zhen Liu, Zhiyuan Chen, Jianwu Wang, Edward Raff, Enza Messina:
Flexible and Adaptive Fairness-aware Learning in Non-stationary Data Streams. ICTAI 2020: 399-406 - [i6]Wenbin Zhang, Liming Zhang, Dieter Pfoser, Liang Zhao:
Disentangled Dynamic Graph Deep Generation. CoRR abs/2010.07276 (2020) - [i5]Wenbin Zhang, Liang Zhao:
Online Decision Trees with Fairness. CoRR abs/2010.08146 (2020) - [i4]Xuejiao Tang, Liuhua Zhang, Wenbin Zhang, Xin Huang, Vasileios Iosifidis, Zhen Liu, Mingli Zhang, Enza Messina, Ji Zhang:
Using Machine Learning to Automate Mammogram Images Analysis. CoRR abs/2012.03151 (2020) - [i3]Xuejiao Tang, Jiong Qiu, Ruijun Chen, Wenbin Zhang, Vasileios Iosifidis, Zhen Liu, Wei Meng, Mingli Zhang, Ji Zhang:
A Data-driven Human Responsibility Management System. CoRR abs/2012.03190 (2020)
2010 – 2019
- 2019
- [c10]Xuejiao Tang, Jiong Qiu, Wenbin Zhang, Ibrahim Toure, Mingli Zhang, Enza Messina, Xueping Xie, Xuebing Wang, Sheng Yu:
The Internet of Responsibilities - Connecting Human Responsibilities using Big Data and Blockchain. IEEE BigData 2019: 6226-6228 - [c9]Wenbin Zhang, Xuejiao Tang, Jianwu Wang:
On Fairness-Aware Learning for Non-discriminative Decision-Making. ICDM Workshops 2019: 1072-1079 - [c8]Wenbin Zhang, Eirini Ntoutsi:
FAHT: An Adaptive Fairness-aware Decision Tree Classifier. IJCAI 2019: 1480-1486 - [i2]Wenbin Zhang, Eirini Ntoutsi:
FAHT: An Adaptive Fairness-aware Decision Tree Classifier. CoRR abs/1907.07237 (2019) - 2018
- [c7]Wenbin Zhang, Jianwu Wang:
Content-bootstrapped Collaborative Filtering for Medical Article Recommendations. BIBM 2018: 1184-1188 - [c6]Wenbin Zhang, Jianwu Wang, Daeho Jin, Lazaros Oreopoulos, Zhibo Zhang:
A Deterministic Self-Organizing Map Approach and its Application on Satellite Data based Cloud Type Classification. IEEE BigData 2018: 2027-2034 - [c5]Antonio Candelieri, Wenbin Zhang, Enza Messina, Francesco Archetti:
Automated Rehabilitation Exercises Assessment in Wearable Sensor Data Streams. IEEE BigData 2018: 5302-5304 - [i1]Wenbin Zhang, Jianwu Wang, Daeho Jin, Lazaros Oreopoulos, Zhibo Zhang:
A Deterministic Self-Organizing Map Approach and its Application on Satellite Data based Cloud Type Classification. CoRR abs/1808.08315 (2018) - 2017
- [c4]Wenbin Zhang, Jianwu Wang:
A Hybrid Learning Framework for Imbalanced Stream Classification. BigData Congress 2017: 480-487 - [c3]Wenbin Zhang:
PhD Forum: Recognizing Human Posture from Time-Changing Wearable Sensor Data Streams. SMARTCOMP 2017: 1-2 - 2016
- [c2]Wenbin Zhang, Jian Tang, Nuo Wang:
Using the machine learning approach to predict patient survival from high-dimensional survival data. BIBM 2016: 1234-1238 - [c1]Jianwu Wang, Zhichuan Huang, Wenbin Zhang, Ankita Patil, Ketan Patil, Ting Zhu, Eric J. Shiroma, Mitchell A. Schepps, Tamara B. Harris:
Wearable sensor based human posture recognition. IEEE BigData 2016: 3432-3438
Coauthor Index
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