This episode is a highlight clip from our live interview with Ji Liu at the CVPR 2019 conference. Liu discusses the asynchronous decentralized parallel stochastic gradient descent algorithm and how it can be used for the training process of deep learning. View the full interview and more inspiring videos at Robin.ly: http://bit.ly/2lOgFLL
Ji Liu is an assistant professor at the University of Rochester and the Director at Kuaishou Seattle AI Lab. Prior to Kuaishou, he was the Principal Scientist at Tencent. His research interests include Machine Learning, Optimization, Reinforcement Learning with emphasis on big data involved scenarios. Professor Liu is also interested in applying technology to solve real world problems in the area of image analysis, game AI design, vision understanding, etc. The asynchronous parallel algorithm he proposed has been widely used in many machine learning platforms, such as Google’s TensorFlow. In 2018, he was also named “Innovator Under 35 in China” by MIT.