machine learning

Friday, September 15, 2017 - 9:00am - 10:00am
Michael Kosorok (University of North Carolina, Chapel Hill)
Estimating individualized treatment rules is a central task of personalized or precision medicine. In this presentation, we review several new developments in outcome weighted learning for identifying individualized treatment rules for two challenging settings: dose finding and treatment selection under right censoring. In the former, we develop an approach which involves the use of two different kernels; and in the later, we use random forests to address censoring before applying outcome weighted learning.
Monday, February 22, 2016 - 1:15pm - 2:00pm
Stephen Wright (University of Wisconsin, Madison)
We survey some developments in machine learning and data analysis,
focusing on those in which optimization is an important
component. Some of these have possible relevance for industrial and
energy applications, for example, constraints and covariances could be
learned from process data rather than specified a priori. Some
possibilities along these lines will be proposed.


Subscribe to RSS - machine learning