Speaker: Minghong Fang Date: Feb 28, 11:45am–12:45pm Abstract: Federated learning is a distributed machine learning approach that enables multiple clients (e.g., smartphones, IoT devices, and edge devices) to collaboratively learn a model with help of a server,...
Speaker: Yi Zhu Date: Feb 27, 11:45am–12:45pm Abstract: Autonomous vehicles (AVs) are visioned as a revolutionary power for future transportation. A fundamental function of AV systems is perception, which aims to understand the surrounding driving environment using...
Speaker: Fnu Suya Date: Feb 26, 11:45am–12:45pm Abstract: Machine learning models are often vulnerable to attacks during both training and test phases, yet the risks in adversarial environments are frequently misjudged. In this talk, I will first demonstrate that...
Speaker: Yang Zhou Date: Feb 23, 11:45am–12:45pm Abstract: Machine learning (ML), a powerful tool for automatically extracting, managing, inferencing, and transferring knowledge, has been proven to be extremely useful in understanding the intrinsic nature of...
Speaker: Peizhong Ju Date: Feb 21, 11:45am–12:45pm Abstract: Machine Learning (ML), a vital branch of Artificial Intelligence (AI), has seen rapid advancements in recent years. As ML continues to evolve, it faces two major challenges: the need for deeper theoretical...
