A Theory of Learning from Different Domains (Publisher's PDF)
Shai Ben-David, John Blitzer, Koby Crammer, Alex Kulesza, Fernando Pereira, and Jennifer Wortman Vaughan
To appear in Machine Learning Journal (Special Issue on Learning from Multiple Sources), 2009

The True Sample Complexity of Active Learning
Maria-Florina Balcan, Steve Hanneke, and Jennifer Wortman Vaughan
To appear in Machine Learning Journal (Special issue on COLT 2008), 2009

Behavioral Experiments on Biased Voting in Networks (Publisher's PDF)
Michael Kearns, Stephen Judd, Jinsong Tan, and Jennifer Wortman
Proceedings of the National Academy of Sciences, Volume 106, Number 5, Pages 1347-1352, 2009

Maintaining Equilibria During Exploration in Sponsored Search Auctions (Publisher's Page)
John Langford, Lihong Li, Yevgeniy Vorobeychik, and Jennifer Wortman
To appear in Algorithmica (Special issue on WINE 2007), 2009

Regret to the Best Vs. Regret to the Average (Publisher's Page)
Eyal Even-Dar, Michael Kearns, Yishay Mansour, and Jennifer Wortman
Machine Learning Journal (Special issue on COLT 2007), Volume 72, Numbers 1-2, Pages 21-37, 2008

Learning from Multiple Sources (Publisher's PDF)
Koby Crammer, Michael Kearns, and Jennifer Wortman
Journal of Machine Learning Research, Volume 9, Pages 1757-1774, 2008

Censored Exploration and the Dark Pool Problem (PDF)
Kuzman Ganchev, Michael Kearns, Yuriy Nevmyvaka, and Jennifer Wortman Vaughan
In the 25th Conference on Uncertainty in Artificial Intelligence (UAI 2009)
Winner of the Best Student Paper Award at UAI

Learning from Collective Behavior (PDF)
Michael Kearns and Jennifer Wortman
In the 21st Annual Conference on Learning Theory (COLT 2008)

The True Sample Complexity of Active Learning (PDF)
Maria-Florina Balcan, Steve Hanneke, and Jennifer Wortman
In the 21st Annual Conference on Learning Theory (COLT 2008)
Winner of the Mark Fulk Best Student Paper Award at COLT
A preliminary version appeared in the NIPS 2007 Workshop on Principles of Learning Problem Design

Complexity of Combinatorial Market Makers (PDF)
Yiling Chen, Lance Fortnow, Nicolas Lambert, David Pennock, and Jennifer Wortman
In the Ninth ACM Conference on Electronic Commerce (EC 2008)

Self-Financed Wagering Mechanisms for Forecasting (PDF)
Nicolas Lambert, John Langford, Jennifer Wortman, Yiling Chen, Daniel Reeves, Yoav Shoham, and David Pennock
In the Ninth ACM Conference on Electronic Commerce (EC 2008)
Winner of an Outstanding Paper Award at EC
A preliminary version appeared in the DIMACS Workshop on the Boundary Between Economic Theory and CS

Exploration Scavenging (PDF)
John Langford, Alexander Strehl, and Jennifer Wortman
In the 25th International Conference on Machine Learning (ICML 2008)

Privacy-Preserving Belief Propagation and Sampling (PDF)
Michael Kearns, Jinsong Tan, and Jennifer Wortman
In Advances in Neural Information Processing Systems 20 (NIPS 2007)
Winner of the Best Student Paper Award at the New York Academy of Sciences 2007 Symposium on ML

Learning Bounds for Domain Adaptation (PDF)
John Blitzer, Koby Crammer, Alex Kulesza, Fernando Pereira, and Jennifer Wortman
In Advances in Neural Information Processing Systems 20 (NIPS 2007)

Maintaining Equilibria During Exploration in Sponsored Search Auctions (PDF)
Jennifer Wortman, Yevgeniy Vorobeychik, Lihong Li, and John Langford
In the 3rd International Workshop on Internet and Network Economics (WINE 2007)

Sponsored Search with Contexts (PDF)
Eyal Even-Dar, Michael Kearns, and Jennifer Wortman
In the 3rd International Workshop on Internet and Network Economics (WINE 2007)
This longer version appeared in the WWW 2007 Third Workshop on Sponsored Search Auctions

Regret to the Best Vs. Regret to the Average (PDF)
Eyal Even-Dar, Michael Kearns, Yishay Mansour, and Jennifer Wortman
In the 20th Annual Conference on Learning Theory (COLT 2007)
Winner of a Best Student Paper Award at COLT
A preliminary version appeared in the NIPS 2006 Workshop on Online Trading of Exploration and Exploitation

Learning from Multiple Sources (PDF)
Koby Crammer, Michael Kearns, and Jennifer Wortman
In Advances in Neural Information Processing Systems 19 (NIPS 2006)

Risk-Sensitive Online Learning (Corrected version, October 2006: PDF)
Eyal Even-Dar, Michael Kearns, and Jennifer Wortman
In the 17th International Conference on Algorithmic Learning Theory (ALT 2006)

Learning from Data of Variable Quality (PDF)
Koby Crammer, Michael Kearns, and Jennifer Wortman
In Advances in Neural Information Processing Systems 18 (NIPS 2005)

Run the GAMUT: A Comprehensive Approach to Evaluating Game-Theoretic Algorithms (PDF)
Eugene Nudelman, Jennifer Wortman, Yoav Shoham, and Kevin Leyton-Brown
In the 3rd International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2004)
Short versions appeared at the Second World Congress of the Game Theory Society (Games 2004) and the 15th Annual Conference on Game Theory (Stony Brook 2004)
Download GAMUT here

Learning from Collective Preferences, Behavior, and Beliefs (PDF)
Jennifer Wortman Vaughan
Doctoral Dissertation, University of Pennsylvania, 2009

Viral Marketing and the Diffusion of Trends on Social Networks (PDF)
Jennifer Wortman
University of Pennsylvania Technical Report MS-CIS-08-19, May 2008
In fulfillment of the Department of Computer and Information Science Written Preliminary Exam II