Mahdi Cheraghchi, Adam Klivans, Pravesh Kothari, and Homin K. Lee
Submodular functions are noise stable.
Proc. of the 23rd Annual ACM-SIAM Symposium on Discrete Algorithms (SODA 2012), to appear.
Electronic Colloquium on Computational Complexity, TR11-090, 2011.

Vitaly Feldman, Homin K. Lee, and Rocco A. Servedio
Lower Bounds and hardness amplification for learning shallow monotone formulas.
Proc. of the 24th Annual Conference on Learning Theory (COLT 2011).
Electronic Colloquium on Computational Complexity, TR10-022, 2010.

Adam Klivans, Homin K. Lee, and Andrew Wan
Mansour's Conjecture is true for random DNF formulas.
Proc. of the 23th Annual Conference on Learning Theory (COLT 2010), pages 368-380, Omnipress, 2010.
Electronic Colloquium on Computational Complexity, TR10-023, 2010.

Homin K. Lee
On the Learnability of Monotone Functions.
Ph.D. Thesis (with distinction), Columbia University, 2009.

Homin K. Lee
Decision trees and influence: an inductive proof of the OSSS inequality.
Theory of Computing, 6(4):81-84, 2010.

Shiva Kasiviswanathan, Homin K. Lee, Kobbi Nissim, Sofya Raskhodnikova, and Adam Smith
What can we learn privately?
SIAM Journal on Computing, 40(3): 793-826, 2011.
Preliminary version in Proc. of the IEEE Symposium on Foundations of Computer Science (FOCS 2008).

Ilias Diakonikolas, Homin K. Lee, Kevin Matulef, Rocco A. Servedio, and Andrew Wan.
Efficiently testing sparse GF(2) polynomials.
Algorithmica, 61(3):580-605, 2011.
Preliminary version in Proc. of the International Colloquium on Automata, Languages and Programming (ICALP 2008).

D. Dachman-Soled, H. K. Lee, T. Malkin, R. A. Servedio, A. Wan, and H. Wee.
Optimal cryptographic hardness of learning monotone functions.
Theory of Computing, 5(13):257-282, 2009.
Preliminary version in Proc. of the International Colloquium on Automata, Languages and Programming (ICALP 2008).

Jeffrey Jackson, Homin K. Lee, Rocco A. Servedio, and Andrew Wan.
Learning random monotone DNF.
Discrete Applied Mathematics, 159(5):259-271, 2011.
Electronic Colloquium on Computational Complexity, TR07-129, 2007.
Preliminary version in Proc. of the 12th International Workshop on Randomization and Computation (RANDOM 2008).

Homin K. Lee, Tal Malkin, and Erich Nahum.
Cryptographic strength of SSL/TLS servers: current and recent practices.
Proc. of the 7th ACM SIGCOMM Conference on Internet Measurement (IMC 2007),
pages 83-92, ACM Press, 2007.

I. Diakonikolas, H. K. Lee, K. Matulef, K. Onak, R. Rubinfeld, R. A. Servedio, and A. Wan.
Testing for concise representations.
Electronic Colloquium on Computational Complexity, TR07-077, 2007.
Preliminary version in Proc. of the 48th Annual IEEE Symposium on Foundations of Computer Science (FOCS 2007).

Homin K. Lee, Rocco A. Servedio, and Andrew Wan.
DNF are teachable in the average case.
Machine Learning, 69(2-3):79-96, 2007.
Preliminary version in Proc. of the 19th International Conference on Learning Theory (COLT 2006).
Mark Fulk Best Student Paper Award

Homin K. Lee, William Braynen, Kiran Keshav, and Paul Pavlidis.
ErmineJ: Tool for functional analysis of gene expression data sets.
BMC Bioinformatics, 6:269, 2005.

Ariel Elbaz, Homin K. Lee, Rocco A. Servedio, and Andrew Wan.
Separating models of learning from correlated and uncorrelated data.
Journal of Machine Learning Research, 8(Feb):277-290, 2007.
Preliminary version in Proc. of the 18th International Conference on Learning Theory (COLT 2005).

Ted Diament, Homin K. Lee, Angelos Keromytis, and Moti Yung.
The efficient dual receiver cryptosystem and its applications.
International Journal of Network Security, 13(3):135-151, 2011. Preliminary version in Proc. of the 11th ACM Conference on Computer and Communications Security (CCS 2004).

Homin K. Lee, Amy K. Hsu, Jon Sajdak, Jie Qin, and Paul Pavlidis.
Coexpression analysis of human genes across many microarray data sets.
Genome Research, 14(6):1085-1094, 2004.

A. L. Yonan, A. A. Palmer, K. C. Smith, I. Feldman, H. K. Lee, J. M. Yonan, S. G. Fischer, P. Pavlidis, and T. C. Gilliam.
Bioinformatic analysis of autism positional candidate genes using biological databases and computational gene network prediction.
Genes, Brain and Behavior, Oct;2(5):303-320, 2003.