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Proposed a novel model-free label-flipping attack based on the multi-modality of the data and a novel defense technique based on the Synthetic Reduced Nearest Neighbor (SRNN) model. A preprint copy […]

SAIL Lab in collaboration with Enterprise Model Risk Management Group, Royal Bank of Canada (RBC) did research project on Deep Reinforcement Learning(DRL). The paper titled “Adversarial Attacks on Deep Algorithmic […]

Milan Zinzuvadiya’s research work under the supervision of Dr. Behzadan, titled “State-Wise Adaptive Discounting from Experience (SADE): A Novel Discounting Scheme for Reinforcement Learning” has been accepted by AAAI Conference […]

Dr. Behzadan’s paper with Dr. Ibrahim Baggili, titled “Founding the domain of AI Forensics” has been accepted for presentation at SafeAI 2020. A preprint copy of this paper is available […]

We hosted the first symposium of AI and Data Science Research at the University of New Haven.

The Secure and Assured Intelligent Learning (SAIL) lab is now the most recently established research group at the University of New Haven