אירועים והרצאות בפקולטה למדעי המחשב ע"ש הנרי ומרילין טאוב

In this talk, we will discuss recent advances in multitask regression and their application to flood forecasting. We will begin with a brief overview of Google’s flood forecasting initiative in India. The project involves time series prediction in different geographical locations based on a limited number of heavy tailed samples. To address these challenges, we will consider non-convex robust multitask models based on elliptical distributions. Next, we will present a spectral algorithm for learning shared features for multiple related tasks. Both works are accompanied by theoretical analysis and experiments with real world data.

Short Bio:
Ami Wiesel received the B.Sc. and M.Sc. degrees in electrical engineering from Tel-Aviv University, Tel-Aviv, Israel, in 2000 and 2002, respectively, and the Ph.D. degree in Electrical Engineering from the Technion-Israel Institute of Technology, Haifa, Israel, in 2007. He was a Postdoctoral Fellow in the Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA, during 2007–2009. He is currently an Associate Professor in the Rachel and Selim Benin School of Computer Science and Engineering, Hebrew University, Jerusalem, Israel. Since 2018, he is also a Visiting Researcher in Google.