Andres Muñoz MedinaAddress: 251 Mercer Street
New York, NY, 10012
Email: munoz at cims dot nyu dot edu
Current Research:I am currently involved in several fascinating research projects Mostly, I am interested on connections between Game Theory and Machine Learning, such as revenue optimization in Generalized Second-Price Auctions and learning against adversarial buyers. I am also working on discrepancy minimization algorithms for domain adaptation as well as analysis and algorithm design for bandit problems.
I am a PhD student at the Courant Institute of Mathematical sciences, I am interested in machine learning, statistics and algorithms. My advisor is Professor Mehryar Mohri. My current research is focused on learning theory applied to market algorithms and auctioning. I am however interested in domain adaptation and regret minimization algorithms.
I am the organizer of the Courant Machine Learning Seminar and was president of the Courant Student Organization which is in charge of promoting Courant PhD students to industry as well as community outreach events such as CSplash . In the past three years I have been a research intern at Google working on large scale implementation of learning algorithms.
When I am not doing research I like to bike, run, swim and travel.
Mehryar Mohri and Andres Muñoz Medina Revenue Optimization in Posted-Price Auctions with Strategic Buyers
To appear in NIPS 2014.
Mehryar Mohri and Andres Muñoz Medina. Learning Theory and Algorithms for Revenue Optimization in Second-Price Auctions with Reserve. In Proceeding of the 31st International Conference on Machine Learning.
Beijing China, June 2012. JMLR.
Corinna Cortes, Mehryar Mohri and Andres Muñoz Medina Adaptation Algorithm and Theory Based on Generalized Discrepancy
Mehryar Mohri and Andres Muñoz Medina. New Analysis and algorithm for learning with drifting distributions. In Proceedings of the 23rd International Conference on Algorithmic Learning Theory (ALT 2012). Lyon France, October 2012. Springer, Heidelberg, Germany.