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Privacy Awareness, Responsibility and Trustworthy Lab
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Profile (261) | Event (5) | Page (3) | News Article (1) | Plain Page (1)
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KAUST-CEMSE-CS-PhD-Dissertation-Defense-Xiaochuan-Gou-Explainability-and-Efficiency-in-Spatio-Temporal-Models
Jul 6, 15:00 - 18:00, Explainability and Efficiency in Spatio-Temporal Models: Applications to Traffic Forecasting (B5 L5 R5209), Xiaochuan Gou, Ph.D. Student, Computer Science
Graph Neural Networks, model interpretability, traffic forecasting, Ph.D. Dissertation Defense
KAUST-CEMSE-CS-PhD-Dissertation-Defense-Lijie-Zihang Xiang-Modern-Privacy-preserving-Machine-Learning
Jul 6, 10:00 - 12:00, Modern Privacy-preserving Machine Learning: Rigorous Approach for Data Privacy (B3 L5 R5216), Zihang Xiang, Ph.D. Student, Computer Science
Differential privacy, Federated learning, privacy-preserving machine learning, Ph.D. Dissertation Defense
KAUST CEMSE CS Ph.D. Dissertation Defense Cheng-Long Wang Provable and Measurable Machine Unlearning in Modern Learning Systems
Mar 10, 10:30 - 12:30, Provable and Measurable Machine Unlearning in Modern Learning Systems (B2 L5 R5209), Cheng-Long Wang, Ph.D. Student, Computer Science
AI, Data Privacy, Federated learning, machine learning, Machine Unlearning, Trustworthy AI, Ph.D. Dissertation Defense
May 8, 13:00 - 14:00, Spatiotemporal Machine Learning for Real-world Complex Systems: Enhancing Smart Transportation with Robust AI (B1 L4 R4214), ZIyue Li, Assistant Professor, Information Systems Department, University of Cologne, Germany
Seminar
KAUST-CEMSE-AMCS-PhD-Dissertation-Defense-Lijie-Hu-Towards-Usable-and-Useful-Explainable-A
Jul 7, 17:00 - 19:00, Towards Usable and Useful Explainable AI (B3 L5 R5220), Lijie Hu, Ph.D. Student, Computer Science
explainable AI, Large Language Models, multimodal models, Ph.D. Dissertation Defense

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