A Practical Method for Solving Contextual Bandit Problems Using Decision Trees

no code implementations • 14 Jun 2017 • Adam N. Elmachtoub, Ryan McNellis, Sechan Oh, Marek Petrik

We propose a new method for the contextual bandit problem that is simple, practical, and can be applied with little or no domain expertise.

Thompson Sampling

Building an Interpretable Recommender via Loss-Preserving Transformation

no code implementations • 19 Jun 2016 • Amit Dhurandhar, Sechan Oh, Marek Petrik

We propose a method for building an interpretable recommender system for personalizing online content and promotions.

Classification General Classification +2