Making Good Decisions Using Data-driven Models

ALS 4001 ** note the different time and place **
Tue, 03/15/2016 - 9:00am

Marek Petrik
Research Staff Member, Solutions and Mathematical Sciences Department, IBM T.
J. Watson Research Center

Abstract:
Decision-making based on data-driven models is becoming increasingly
important as data collection improves and machine learning matures. Because
data-driven models are often imprecise, recommended actions may appear good
in simulation but fail when deployed.  We develop decision-making methods
that explicitly address model imprecision in reinforcement learning. In this
talk, I will describe algorithms that leverage robust optimization to reduce
the impact of model error on quality of decisions. I will address both model
bias and variance and will discuss applications to problems in energy
storage, agriculture, and others.

Bio:


URL:
http://eecs.oregonstate.edu/colloquium/making-good-decisions-using-data-driven-models

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