Center for Advanced Intelligence Project

Our main goal is to understand the principles of learning from data and use them to develop algorithms that can learn like living beings. Our current focus is on sequential learning and exploration. We are working on problems in several areas of machine learning, such as approximate inference, deep learning, reinforcement learning, active learning, online learning, and reasoning in computer vision. In our recent works, we have combined ideas from a wide range of fields, such as, optimization, Bayesian statistic, information geometry, signal processing, and control systems.