College of Computing (CSE)Georgia Institute of Technology
Email:
Office: 1305 KACB
Resume: [PDF]
I am currently a PhD student at College of Computing, Georgia Tech. Prior to that, I obtained my Masters degree in 2010. I work with Prof. Guy Lebanon. I received my Bachelors degree from Madras Institute of Technology in 2008. As an undergrad, I worked on wireless communications and information theory. Yes, I select text while reading :)
Research
I am interested in several aspects of statistical machine learning. Specific research interests include:
- Estimation procedures for complex, high dimensional data.
- Labeling complexity reduction methods (for classification, regression and structured prediction) and its theoretical analysis.
Papers
-
Journals
-
Unsupervised Supervised Learning II: Margin-Based Classification without Labels. [Link]
K. Balasubramanian, P. Donmez, G. Lebanon.
Journal of Machine Learning Research (JMLR) 12, pp. 3119-3145, 2011. -
Unsupervised Supervised Learning I: Estimating Classification and Regression Errors without Labels. [Link]
P. Donmez, G. Lebanon, K. Balasubramanian.
Journal of Machine Learning Research (JMLR) 11, pp. 1323-1351, 2010.
Conferences -
Unsupervised Supervised Learning II: Margin-Based Classification without Labels. [PDF] [arXiv link]
K. Balasubramanian, P. Donmez, G. Lebanon.
Proc. of the 14th International Conference on Artificial Intelligence and Statistics (AISTATS) 2011. -
Asymptotic Analysis of Generative Semi-Supervised Learning. [PDF] [arXiv link]
J. V. Dillon, K. Balasubramanian, G. Lebanon.
Proc. of the 27th International Conference on Machine Learning (ICML), 2010. -
Dimensionality Reduction for Text using Domain Knowledge. [PDF] [arXiv link]
Y. Mao, K. Balasubramanian, G. Lebanon.
Proc. of the 23rd International Conference on Computational Linguistics (COLING), 2010.
Misc. -
Learning without labels and nonnegative tensor factorization. [Link]
K. Balasubramanian.
Master's Thesis, Georgia Institute of Technology, 2010. - I try to maintain notes about topics which I find useful/interesting here.
Selected Courses
- Operator Theory (S'12)
- Stochastic Processes and Stochastic Calculus I (F'11)
- Testing Statistical Hypothesis (F'10)
- Advanced Classical Probability Theory (S'10, Audit)
- Non-Linear Optimization (S'09)
- Computational Data Analysis: Foundations of Machine Learning & Data Mining (F'08)
- Numerical Optimization and Applications (F'08)
- Computability and Algorithms(F'08)
Last Modified: Nov 01, 2011