Khai Nguyen
Khai Nguyen
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Dang Nguyen AI Resident at VinAI , Hanoi, Vietnam.
Dang Nguyen is an AI Resident at VinAI , a leading AI research-based company in Vietnam. His current research focuses on Optimal Transport and Model Fusion. He is also interested in Domain Adaptation, Backdoor Attack, and Federated Learning. Prior to joining VinAI, he received his BS degree, summa cum laude, in Information Networking for Innovation and Design from Toyo University. Going further back in time, he is a graduate from High School for Gifted Students, Hanoi University of Science and a Maths Olymp
Max sliced Wasserstein (Max-SW) distance has been widely known as a solution for redundant projections of sliced Wasserstein (SW) distance. In applications that have various independent pairs of probability measures, amortized projection optimization is utilized to predict the “max" projecting directions given two input measures instead of using projected gradient ascent multiple times. Despite being efficient, the first issue of the current framework is the violation of permutation invariance property and
Khai Nguyen
Khai Nguyen