Colloquium Speaker Shie Mannor, Technion, Israel Institute of Technology Monday, October 12, 12:30pm Computer Science 105 Co-hosted by the Computer Science Department and the Center for Statistics and Machine Learning Actionable big data: from data to decisions and back In many sequential decision problems all that we have is a record of historical trajectories. Building dynamic models from these trajectories and ultimately sequential decision policies may result in much uncertainty and bias. In this talk we consider the question of how to create control policies from existing historical data and how to better sample trajectories so that future control policies would be better. This question has been central in reinforcement learning in the last decade if not more, and involves methods from statistics, machine learning, optimization, and control theory. I will start my talk with demonstrating why planning with parameter uncertainty is an important issue. I will then describe several approaches: Bayesian uncertainty model over the unknown parameters, a robust approach that takes a worst case view, and a frequentist approach. I will then discuss the challenges that are posed when the model itself rather than just the parameters may not be fully known. I will then describe two challenging real-world domains that have been studied in my research group in collaboration with experts from industry and academia: diabetes care management in healthcare and asset management in high-voltage transmission grids. For each domain I will describe our efforts to reduce the problem to its bare essentials as a reinforcement learning problem, the algorithms for learning the control policies, and some of the lessons we learned. I graduated from the Technion with a BSc in Electrical Engineering and BA in mathematics (both summa cum laude) in 1996. After that I spent almost four years as an intelligence officer with the Israeli Defense Forces. I was subsequently involved in a few ventures in the high-tech industry. I earned my PhD in Electrical Engineering from the Technion at 2002, under the supervision of Nahum Shimkin. I was then a Fulbright postdoctoral associate with LIDS (MIT) working with John Tsitsiklis for two years. I was at the Department of Electrical and Computer Engineering in McGill University from July 2004 until August 2010, where I held a Canada Research Chair in Machine Learning from 2005 to 2009. I have been with the Department of Electrical Engineering at the Technion since 2008 where I am a professor. I am married to Tally and father to Liam, Oliver and Dylan.