Fri, 29-Oct-2021 / 1:00pm / TBA
In this talk, I will present the universal probability approach to a statistical task. This approach gives us general principles and guidelines for assigning sequential probabilities to data (based on which a statistical decision can then be made), and has been used successfully over the years to problems in compression and estimation among others. I will illustrate this approach via two example applications—sequential prediction and portfolio selection with side information.
Based on joint work with Jongha Jon Ryu and Young-Han Kim.
Alankrita Bhatt is a PhD student in the department of electrical and computer engineering, at the University of California San Diego. Her research interests lie broadly in the field of information theory. Prior to joining UCSD, she received a bachelor’s degree in electrical engineering from the Indian Institute of Technology Kanpur.
Packard Building
Electrical Engineering Department
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Stanford, CA 94305-9515
