Faculty profile 2
Ravikumar's research interests are in statistical machine learning broadly, with particular areas of interest including high-dimensional data analysis, sparse signal recovery, graphical models and optimization.
Sloan Research Fellowship, 2014.
NSF CAREER Award, 2012.
Honorable Mention, ACM SIGKDD Dissertation Award, 2008.
Honorable Mention, CMU School of Computer Science Distinguished Dissertation Award, 2007/08.
Siebel Scholarship, 2007.
Graphical Models via Univariate Exponential Family Distributions. E. Yang, P. Ravikumar, G. Allen, Z. Liu. Journal of Machine Learning Research (JMLR), 2015 (to appear).
Closed-form Estimators for High-dimensional Generalized Linear Models .
E. Yang, A. Lozano, P. Ravikumar. In Advances in Neural Information Processing Systems (NIPS) 28, 2015.
QUIC: Quadratic Approximation for Sparse Inverse Covariance Estimation. C.-J. Hsieh, M. Sustik, I. Dhillon, P. Ravikumar. Journal of Machine Learning Research (JMLR), Vol. 15, pages 2911-2947, 2014.
A Dirty Model for Multiple Sparse Regression. A. Jalali, P. Ravikumar, S. Sanghavi.IEEE Transactions on Information Theory, Vol. 59, No. 12, pages 7947-7968, 2013.
A Unified Framework For High-Dimensional Analysis of M-Estimators with Decomposable Regularizers. S. Negahban, P. Ravikumar, M. J. Wainwright and B. Yu. Statistical Science, Vol. 27, No. 4, pages 538-557, 2012.
• Machine Learning Journal.
Conference Program Chair
• AISTATS 2013, Sixteenth International Conference on Artificial Intelligence and Statistics.