Selected Publications in Chronological Order - (by research area)

(Papers are ordered in reverse chronological order of first publication.)

• Improved Equilibria via Public Service Advertising.
  With Avrim Blum and Yishay Mansour. July 2008.
  
  

• Approximate Clustering without the Approximation.
  With Avrim Blum and Anupam Gupta. July 2008.
  
  

• Random Sampling Auctions for Limited Supply.
  With Nikhil Devanur, Jason D. Hartline, and Kunal Talwar. Technical Report, CMU-CS-07-154, 2007.
  
  

• A Discriminative Framework for Clustering via Similarity Functions.
  With Avrim Blum and Santosh Vempala. STOC 2008.
  

• Item Pricing for Revenue Maximization.
  With Avrim Blum and Yishay Mansour. ACM Conference on Electronic Commerce, 2008.

• Improved Guarantees for Learning via Similarity Functions.
  With Avrim Blum and Nathan Srebro. COLT 2008.
  
  A related note on Similarity-Based Theoretical Foundation for Sparse Parzen Window Prediction.
  With Avrim Blum and Nathan Srebro. ICML/UAI/COLT 2008 Workshop on Sparse Optimization and Variable Selection.

• The True Sample Complexity of Active Learning.
  With Steve Hanneke and Jennifer Wortman. COLT 2008.
  Winner of the Mark Fulk Best Student Paper Award.
  

• Clustering with Interactive Feedback.
  With Avrim Blum. ALT 2008.
  

• New Theoretical Frameworks for Machine Learning.
  Thesis Proposal, May 2007.
  
  
• Margin Based Active Learning.
  With Andrei Broder and Tong Zhang. COLT 2007.
  
  
• A Theory of Loss-leaders: Making Money by Pricing below Cost.
  With Avrim Blum, Hubert Chan, and MohammadTaghi Hajiaghayi. WINE 2007. Also available as Technical Report, CMU-CS-07-143.
  
  
• Robust Reductions from Ranking to Classification.
  With Nikhil Bansal, Alina Beygelzimer, Don Coppersmith, John Langford, and Greg Sorkin. COLT 2007. Invited to appear in a special issue of Machine Learning Journal.
  
  
• Asymptotic Active Learning.
  With Eyal Even-Dar, Steve Hanneke, Michael Kearns, Yishay Mansour, and Jennifer Wortman. NIPS 2007 Workshop on Principles of Learning Design Problem.
  
  
• Open Problems in Efficient Semi-Supervised PAC Learning.
  With Avrim Blum. COLT 2007.
  
  
• Mechanism Design, Machine Learning, and Pricing Problems.
  With Avrim Blum.SIGecom Exchanges 2007, special issue on Combinatorial Auctions (invited).
  
  

• An Augmented PAC Model for Semi-Supervised Learning.
  With Avrim Blum. Book Chapter in Semi-Supervised Learning, Chapelle, O., Zien, A., and Scholkopf, B. (Eds.), MIT Press, 2006.
  
  
• On a Theory of Learning with Similarity Functions.
  With Avrim Blum. ICML 2006.
  
  Combined with subsequent paper by Nathan Srebro in journal version, invited to appear in a special issue of Machine Learning Journal.
  
  
• Agnostic Active Learning.
  With Alina Beygelzimer and John Langford. ICML 2006. Invited to appear in a special issue on Learning Theory of the Journal of Computer and System Sciences.
  
  
• Approximation Algorithms and Online Mechanisms for Item Pricing.
  With Avrim Blum. Theory of Computing 2007. An extended abstract appears in ACM Conference on Electronic Commerce, 2006.
  
  

• A PAC-style Model for Learning from Labeled and Unlabeled Data.
  With Avrim Blum. COLT 2005.
  
  
• Search and Knowledge Representation in Artificial Intelligence. Theory and Applications.
  With Florentina Hristea. University of Bucharest Publishing House, 2005 (in Romanian).
  
  
• Mechanism Design via Machine Learning.
  With Avrim Blum, Jason D. Hartline, and Yishay Mansour. Proceedings of the 46th Annual Symposium on Foundations of Computer Science (FOCS) 2005.
  
  Extended version appears under the title Reducing Mechanism Design to Algorithm Design via Machine Learning in a special issue on Learning Theory of Journal of Computer and System Sciences 2007 (invited).
  
  A related paper on Sponsored Search Auction Design via Machine Learning appears in the Workshop on Sponsored Search Auctions, 2005.
  
  
• Person Identification in Webcam Images: An Application of Semi-Supervised Learning.
  With Avrim Blum, Pakyan Choi, John Lafferty, Brian Pantano, Mugizi Rwebangira, and Xiaojin Zhu. ICML 2005 Workshop on Learning with Partially Classified Training Data.
  
  

• On Kernels, Margins, and Low-dimensional Mappings.
  With Avrim Blum and Santosh Vempala. Proceedings of the 15th International Conference on Algorithmic Learning Theory (ALT '04).
  
  Extended version appears under the title Kernels as Features: On Kernels, Margins, and Low-dimensional Mappings in Machine Learning Journal 2006.
  
  
• Co-Training and Expansion: Towards Bridging Theory and Practice.
  With Avrim Blum and Ke Yang. NIPS 2004.
  
  

• Handwritten Text Localization in Skewed Documents.
  With Ergina Kavallieratou, Doru Balcan, and Nikos Fakotakis. International Conference on Image Processing (ICIP) 2001.
  
  
• An Adaptive Resonance Theory (ART) Based Approach to Handwritten/ Machine-Printed Text Discrimination.
  With Doru Balcan. ICC&IE 2001.