Michael Jordan

Professor of Statistics and Computer Science
Keywords: controls
Research Areas: statistics, electrical engineering, computer science, machine learning, applied statistics, bioinformatics, artificial intelligence, optimization
Website: http://www.cs.berkeley.edu/~jordan/

Research Description:
Hierarchical control and reinforcement learning, optimal feedback (motor coordination), neural networks.

Selected Publications:

  • Jordan, M. I. Graphical models, Statistical Science, 19, 140-155, 2004.
  • Todorov, E., & Jordan, M. I. Optimal feedback control as a theory of motor coordination. Nature Neuroscience, 5, 1226-1235, 2002.
  • Houde, J., & Jordan, M. I. Adaptation in speech production. Science, 279, 1213-1216, 1998.
  • Ghahramani, Z., Wolpert, D., & Jordan, M. I. Generalization to local remappings
    of the visuo-motor coordinate transformation. Journal of Neuroscience, 16, 7085-7096, 1996.
  • Wolpert, D., Ghahramani, Z., & Jordan, M. I. An internal forward model for sensorimotor integration. Science, 269, 1880–1882, 1995.
  • D’Aspremont, A., El Ghaoui, L., Jordan, M. I., & Lanckriet, G. R. G. A direct formulation for sparse PCA using semidefinite programming. SIAM Review, 49, 434- 448, 2007.
  • Teh, Y. W., Jordan, M. I., Beal, M. J., & Blei, D. M. Hierarchical Dirichlet processes. Journal of the American Statistical Association, 101, 1566-1581, 2006.
  • Bartlett, P., Jordan, M. I., & McAuliffe, J. D. Convexity, classification and risk bounds. Journal of the American Statistical Association, 101, 138-156, 2006.
  • McAuliffe, J. D., Jordan, M. I. & Pachter, L. Subtree power analysis and species selection for
    comparative genomics. Proceedings of the National Academy of Sciences, 102, 7900-7905, 2005.
  • Blei, D., Ng, A., & Jordan, M. I. Latent Dirichlet allocation. Journal of Machine Learning Research, 3, 993-1022, 2003.
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