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Education:
- 2002-2007 : PhD in Statistics, University of Michigan. Advisor: George Michailidis
- 1997-2001 : BS Dual Major in Mathematics and Computer Science, Canisius College.
Research Interests:
- Statistical Computing
- Statistical Machine Learning
- Bioinformatics
Publications:
- Culp M., Michailidis G."A co-training algorithm for multi-view data with applications in data fusion." Journal of Chemometrics. To Appear. 2009. [pdf][pkg]
- Culp M., Michailidis G, Johnson K."On Multi-view Learning with Additive Models." Annals of Applied Statistics. 3(1):292--318, 2009. [pdf]
- Culp, M., Michailidis G. "An Iterative Algorithm for Extending Learners to a Semi-supervised Setting." Journal of Computational Graphics and Statistics. 17(3):1--27. 2008. [pdf][doc][code]
- Culp, M., Michailidis G. "Graph-based semi-supervised learning." IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(1):174--179, 2008. [pdf] [pkg]
- Culp, M., Michailidis G., Johnson K. "ada: An R Package for Stochastic Boosting." Journal of Statistical Software. 17(2), 2006. [pdf][pkg]
Other:
- Culp, M. "Multi-view Learning with Additive Models on Graphs." University of Michigan Doctorial Thesis. 2007. [pdf]
Software:
- spa --This site contains information about the implementation for the Sequential Predictions Algorithm.
- cftf --This site contains the co-FTF algorithm.
- ada--This site contains information about an R package for performing discrete boost, real boost, and gentle boost using both exponential and logistic loss.
Teaching: