Machine Learning NYC

Established: December 12, 2012

Research of the Machine Learning group at MSR-NYC spans a wide variety of topics within theoretical and applied machine learning, including learning from interactive data (e.g., contextual bandits), large-scale machine learning, and convex optimization.




Multiworld Testing

Established: November 1, 2013

Exponentially better than A/B testing. Multiworld Testing (MWT) is the capability to test and optimize over K policies (context-based decision rules) using an amount of data and computation that scales logarithmically in K, without…

Explore-Exploit Learning @MSR-NYC

Established: October 24, 2013

This is an umbrella project for machine learning with explore-exploit tradeoff: the trade-off between acquiring and using information. This is a mature, yet very active, research area studied in Machine Learning, Theoretical Computer Science, Operations Research, and Economics. Much of…