Selected Presentations

• Active and Passive Learning of Linear Separators, ITA 2013.

• Finding Endogenously Formed Communities, SODA 2013.

• Distributed Learning, Communication Complexity, and Privacy, COLT 2012.

• Robust Interactive Learning, COLT 2012.

• Learning Valuation Functions
  • PRiML Seminar, University of Pennsylvania. April 2013.
  • Harvard University, Economics and Computer Science Seminar. January 2013.
  • COLT 2012 (see this version).
  • Microsoft Research New England, August 2011.
  • Learning Theory Workshop at FOCM, July 2011.
  • Workshop on Innovations in Algorithmic Game Theory, May 2011.

• Robust Hierarchical Clustering
  • NIPS 2010 Workshop on Robust Statistical Learning.
  • COLT 2010.

• Learning Submodular Functions
  • STOC 2011.
  • The 5th Bertinoro Workshop on Random(ized) Graphs and Algorithms. May 2010
  • SIAM Conference on Discrete Mathematics. June 2010.
  • NIPS 2009 Workshop on Discrete Optimization in Machine Learning. December 2009.

• Circumventing the Price of Anarchy: Leading Dynamics to Good Behavior, ICS 2010.

• Sample Complexity of Active Learning
  • NIPS 2009 Workshop on Adaptive Sensing, Active Learning and Experimental Design: Theory, Methods and Applications.

• Approximate Clustering Without the Approximation
  • Microsoft Research Redmond, July 2010.
  • IBM Research Yorktown, December 2009.
  • INFORMS, October 2009.
  • Barriers in Computational Complexity Workshop, August 2009.
  • SODA 2009 (see this version).

• Improved Equilibria via Public Service Advertising, SODA 2009.

• Clustering with Interactive Feedback , ALT 2008.

• New Theoretical Frameworks for Machine Learning, Thesis Defense, August 2008.

• A Discriminative Framework for Clustering via Similarity Functions, STOC 2008.

• A Theory of Learning and Clustering via Similarity Functions, China Theory Week, September 2007.

• Item Pricing for Revenue Maximization in Combinatorial Auctions, Dagsthul Workshop on Computational Social Systems and the Internet, July 2007.

• Margin Based Active Learning, COLT 2007.

• Thesis Proposal, CMU, May 2007.

• Mechanism Design, Machine Learning and Pricing Problems
  • Second Bertinoro Workshop on Algorithmic Game Theory (AGATE 2006).
  • University of California at San Diego, October 2006.
  
  
• On Learning with Similarity Functions
  • Mathematical Foundations of Learning Theory Conference, May 2006.
  • ICML 2006.
  
  
• Approximation Algorithms and Online Mechanisms for Item Pricing, EC 2006.
  
  
• Mechanism Design via Machine Learning
  • FOCS 2005.
  • NIPS 2005 Workshop on Value of Information in Inference, Learning and Decision-Making.

• An Augmented PAC Model for Semi-Supervised Learning
  • Toyota Technological Institute at Chicago (TTI-C), August 2005.
  • COLT 2005.
  • IBM Research T.J. Watson, June 2005.
  • Microsoft Research Silicon Valley, May 2005.
  • NIPS 2004 Workshop on (Ab)Use of Bounds.
  • Mathematical Foundations of Learning Theory Conference, June 2004.


• Sponsored Search Auctions Design via Machine Learning, ACM-EC 2005 Workshop on Sponsored Search Auctions.
  
  
• Co-Training and Expansion: Towards Bridging Theory and Practice, NIPS 2004.
  
  
• On Kernels, Margins, and Low-dimensional Mappings
  • IBM Research T.J. Watson, July 2005.
  • CMU Theory Lunch, March 2004.