What are different techniques for privacy-preserving machine learning?

Oct 21, 2024 ... Abbas Saad Alatrany, Wasiq Khan, Abir Hussain, Hoshang Kolivand, and Dhiya Al-Jumeily. 2024. An explainable machine learning approach for ... Jul 13, 2010 ... This table reports the N-fold cross-validation test results for the machine learning algorithm and for an “informed guessing” strategy. In the “ ... Professor Zhang's research interests are artificial intelligence, informational ... CSE144 Applied Machine Learning: Deep Learning CSE272 Information ... ... Artificial Intelligence (AI) in transforming business. Covering key areas like machine learning, natural language processing, computer vision, and robotics ... Jul 6, 2023 ... Reinforcement learning (RL) is indispensable for building intelligent decision-making agents. However, current RL algorithms suffer from ... As machines replace humans in financial markets, how is informational efficiency impacted? We shed light on this issue by exploiting unique data that allow ... Proceedings of the 41st International Conference on Machine Learning, PMLR 235:54414-54429, 2024. Abstract. Standard exploration methods typically rely on ... This paper uses machine learning techniques to examine the extent to which firms could identify the bids of their rivals in public data, and to describe the ... Mar 24, 2024 ... AAAI Technical Track on Machine Learning VI. A Twist for Graph Classification: Optimizing Causal Information Flow in Graph Neural Networks ... Sep 15, 2021 ... Here, I outline and consider privacy concerns with commercial healthcare AI, focusing on both implementation and ongoing data security.