Suchergebnisse - "Zhang, Wenbin"

AI Fairness Beyond Complete Demographics: Current Achievements and Future Directions

Autoren: Wang, Zichong Yin, Zhipeng Yap, Roland H.C. et al.

Quelle: ECAI 2025. 413

Toward Adaptive Large Language Models Structured Pruning via Hybrid-grained Weight Importance Assessment

Autoren: Liu, Jun Kong, Zhenglun Zhao, Pu et al.

Quelle: Proceedings of the AAAI Conference on Artificial Intelligence. 39:18879-18887

Schlagwörter: FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Science - Computation and Language, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence, Computation and Language (cs.CL), Machine Learning (cs.LG)

Zugangs-URL: http://arxiv.org/abs/2403.10799

Measurement of Step Angle for Quantifying the Gait Impairment of Parkinson’s Disease by Wearable Sensors: Controlled Study

Autoren: Wang, Jingying Gong, Dawei Luo, Huichun et al.

Quelle: JMIR mHealth and uHealth, Vol 8, Iss 3, p e16650 (2020)

Schlagwörter: Information technology, T58.5-58.64, Public aspects of medicine, RA1-1270

Dateibeschreibung: electronic resource

Relation: http://mhealth.jmir.org/2020/3/e16650/; https://doaj.org/toc/2291-5222

Zugangs-URL: https://doaj.org/article/9d985117d5cd49bc99ea61a63b680573

Online and Customizable Fairness-aware Learning

Autoren: Zhang, Wenbin

Quelle: Knowledge and Information Systems.

Schlagwörter: Machine Learning, FOS: Computer and information sciences, Artificial Intelligence (cs.AI), Artificial Intelligence, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, Machine Learning (cs.LG)

Zugangs-URL: http://arxiv.org/abs/2010.08146

Effects and neural mechanisms of a brain–computer interface-controlled soft robotic glove on upper limb function in patients with subacute stroke: a randomized controlled fNIRS study

Autoren: Ji, Xiang Lu, Xia Xu, Yi et al.

Quelle: J Neuroeng Rehabil

Schlagwörter: Research

Cardiac tumors: clinical presentation, diagnosis, treatment, and results

Autoren: Wang, Chonggang Li, Xiaoyang Yang, Lirui et al.

Quelle: Langenbecks Arch Surg

Schlagwörter: Review

Mitochondrial homeostasis restoring peptide-drug conjugates with ROS-responsive NO releasing ability for targeted therapy of myocardial infarction

Autoren: Lu, Zhaoyang Chai, Quanyou Dai, Wenbin et al.

Quelle: J Nanobiotechnology

Schlagwörter: Research

Association between left ventricular remodeling and coronary chronic total occlusion in hypertensive coronary artery disease patients

Autoren: He, Wujian Yao, Qiang Li, Duanbin et al.

Quelle: Sci Rep

Schlagwörter: Article

Predictors for quantitative flow ratio loss in patients with de novo coronary artery disease treated with drug-coated balloons

Autoren: Zhu, Yunhui Hu, Tianli Bian, Qianqian et al.

Quelle: Sci Rep

Schlagwörter: Article

FedCAP: Robust Federated Learning via Customized Aggregation and Personalization

Autoren: Li, Youpeng Wang, Xinda Yu, Fuxun et al.

Quelle: 2024 Annual Computer Security Applications Conference (ACSAC). :747-760

Schlagwörter: FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Science - Cryptography and Security, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence, Cryptography and Security (cs.CR), Machine Learning (cs.LG)

Zugangs-URL: http://arxiv.org/abs/2410.13083

Trend Analysis and Forecasting Study on the Changing Disease Burden of Rheumatoid Arthritis in China, 1990-2021

Autoren: LING Yao, ZHANG Wenbin, WANG Shihong, CHEN Yongze, DONG Wenjiao, DENG Xingyu, DING Yuanlin

Quelle: Zhongguo quanke yixue, Vol 28, Iss 15, Pp 1914-1922 (2025)

Schlagwörter: arthritis, rheumatoid, global burden of disease, disability adjusted life years, incidence, prevalence, trend analysis, autoregressive moving average mode, Medicine

Dateibeschreibung: electronic resource

Relation: https://www.chinagp.net/fileup/1007-9572/PDF/2024-060178.pdf; https://doaj.org/toc/1007-9572

Zugangs-URL: https://doaj.org/article/cdd979fa6c6745e6ab9736aeed18fadb

Structural and Functional Characterization of the Signaling Molecule Autoinducer-2 Synthesis Enzyme S-Ribosylhomocysteinase in Limosilactobacillus fermentum

Autoren: WEI Guangqiang, WANG Teng, XU Ziqi, WANG Yuzhu, ZHANG Wenbin, LI Xinglun, HUANG Aixiang

Quelle: Shipin Kexue, Vol 46, Iss 7, Pp 135-142 (2025)

Schlagwörter: limosilactobacillus fermentum, s-ribosylhomocysteinase, structural characterization, functional properties, bioinformatics, Food processing and manufacture, TP368-456

Dateibeschreibung: electronic resource

Relation: https://www.spkx.net.cn/fileup/1002-6630/PDF/2025-46-7-016.pdf; https://doaj.org/toc/1002-6630

Zugangs-URL: https://doaj.org/article/433982a60b3a427f95194d2ff1df3b90

Power Load Data Completion Method Based on Integrated Graph Convolutional Variational Transformer

Autoren: YAN Li, HU Hailin, SHI Lei, WU Qinzheng, LÜ Tianguang, XU Yingdong, ZHANG Wenbin, WANG Gaozhou

Quelle: Dianli jianshe, Vol 46, Iss 4, Pp 49-57 (2025)

Schlagwörter: data imputation, graph convolutional networks, transformer model, power load data, Science, Production of electric energy or power. Powerplants. Central stations, TK1001-1841

Dateibeschreibung: electronic resource

Relation: https://www.cepc.com.cn/fileup/1000-7229/PDF/1743057799426-747902974.pdf; https://doaj.org/toc/1000-7229

Zugangs-URL: https://doaj.org/article/ff05df7c2f42471bab25ca3a77bd8fe5

Fairness in Large Language Models: A Taxonomic Survey

Autoren: Chu, Zhibo Wang, Zichong Zhang, Wenbin

Quelle: ACM SIGKDD Explorations Newsletter. 26:34-48

Schlagwörter: FOS: Computer and information sciences, 0301 basic medicine, 03 medical and health sciences, Computer Science - Computation and Language, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, Computation and Language (cs.CL)

Zugangs-URL: http://arxiv.org/abs/2404.01349

AMCR: A Framework for Assessing and Mitigating Copyright Risks in Generative Models

Autoren: Yin, Zhipeng Wang, Zichong Palikhe, Avash et al.

Quelle: ECAI 2025. 413

Schlagwörter: Machine Learning, FOS: Computer and information sciences, Cryptography and Security, Computer Vision and Pattern Recognition (cs.CV), Computer Vision and Pattern Recognition, Cryptography and Security (cs.CR), Machine Learning (cs.LG)

Zugangs-URL: http://arxiv.org/abs/2509.00641

On the Efficiency of Privacy Attacks in Federated Learning

Autoren: Tabassum, Nawrin Chow, Ka-Ho Wang, Xuyu et al.

Quelle: 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). :4226-4235

Schlagwörter: FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Science - Cryptography and Security, Cryptography and Security (cs.CR), Machine Learning (cs.LG)

Zugangs-URL: http://arxiv.org/abs/2404.09430

Performance evaluation of nanofluid-enhanced biomimetic liquid-cooled heat sinks for efficient thermal management applications

Autoren: Babar, Hamza Wu, Hongwei Eltaweel, Mahmoud et al.

Quelle: International Journal of Heat and Mass Transfer. 252:127498

Semi-Supervised Training for Positioning of Welding Seams

Autoren: Zhang, Wenbin

Thesis Advisors: Lang, Jochen

Schlagwörter: Welding seam, Semi-supervised learning, Localization

Dateibeschreibung: application/pdf

Verfügbarkeit: http://hdl.handle.net/10393/42257

Decoupling Bidirectional Geometric Representations of 4D cost volume with 2D convolution

Autoren: Wei, Xiaobao Shu, Changyong Yue, Zhaokun et al.

Schlagwörter: FOS: Computer and information sciences, Computer Vision and Pattern Recognition (cs.CV), Computer Vision and Pattern Recognition

Zugangs-URL: http://arxiv.org/abs/2509.02415

Uncovering the Vulnerability of Large Language Models in the Financial Domain via Risk Concealment

Autoren: Cheng, Gang Jin, Haibo Zhang, Wenbin et al.

Schlagwörter: Machine Learning, FOS: Computer and information sciences, Artificial Intelligence (cs.AI), Artificial Intelligence, Computation and Language, Computation and Language (cs.CL), Machine Learning (cs.LG)

Zugangs-URL: http://arxiv.org/abs/2509.10546