We are Microsoft researchers working on machine learning and reinforcement learning. Ask Dr. John Langford and Dr. Akshay Krishnamurthy anything about contextual bandits, RL agents, RL algorithms, Real-World RL, and more!
We are ending the AMA at this point with over 50 questions answered!
Thanks for the great questions! - Akshay
Thanks all, many good questions. -John
Ask us anything about:
*Latent state discovery
*Real world reinforcement learning
*The role of theory in practice
*The future of machine learning research
John Langford is a computer scientist working in machine learning and learning theory at Microsoft Research New York, of which he was one of the founding members. He is well known for work on the Isomap embedding algorithm, CAPTCHA challenges, Cover Trees for nearest neighbor search, Contextual Bandits (which he coined) for reinforcement learning applications, and learning reductions.
John is the author of the blog hunch.net and the principal developer of Vowpal Wabbit. He studied Physics and Computer Science at the California Institute of Technology, earning a double bachelor’s degree in 1997, and received his Ph.D. from Carnegie Mellon University in 2002.
Akshay Krishnamurthy is a principal researcher at Microsoft Research New York with recent work revolving around decision making problems with limited feedback, including contextual bandits and reinforcement learning. He is most excited about interactive learning, or learning settings that involve feedback-driven data collection.
Previously, Akshay spent two years as an assistant professor in the College of Information and Computer Sciences at the University of Massachusetts, Amherst and a year as a postdoctoral researcher at Microsoft Research, NYC. Before that, he completed a PhD in the Computer Science Department at Carnegie Mellon University, advised by Aarti Singh, and received his undergraduate degree in EECS at UC Berkeley.