Michael I. Jordan
Michael I. Jordan
Professor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC Berkeley
Verified email at cs.berkeley.edu - Homepage
Cited by
Cited by
Latent dirichlet allocation
DM Blei, AY Ng, MI Jordan
Journal of machine Learning research 3 (Jan), 993-1022, 2003
On spectral clustering: Analysis and an algorithm
AY Ng, MI Jordan, Y Weiss
Advances in neural information processing systems, 849-856, 2002
Adaptive mixtures of local experts
RA Jacobs, MI Jordan, SJ Nowlan, GE Hinton
Neural computation 3 (1), 79-87, 1991
Sharing clusters among related groups: Hierarchical Dirichlet processes
YW Teh, MI Jordan, MJ Beal, DM Blei
Advances in neural information processing systems, 1385-1392, 2005
Graphical models, exponential families, and variational inference
MJ Wainwright, MI Jordan
Now Publishers Inc, 2008
An introduction to variational methods for graphical models
MI Jordan, Z Ghahramani, TS Jaakkola, LK Saul
Machine learning 37 (2), 183-233, 1999
Hierarchical mixtures of experts and the EM algorithm
MI Jordan, RA Jacobs
Neural computation 6 (2), 181-214, 1994
Distance metric learning with application to clustering with side-information
EP Xing, MI Jordan, SJ Russell, AY Ng
Advances in neural information processing systems, 521-528, 2003
An internal model for sensorimotor integration
DM Wolpert, Z Ghahramani, MI Jordan
Science 269 (5232), 1880-1882, 1995
Learning the kernel matrix with semidefinite programming
GRG Lanckriet, N Cristianini, P Bartlett, LE Ghaoui, MI Jordan
Journal of Machine learning research 5 (Jan), 27-72, 2004
Trust region policy optimization
J Schulman, S Levine, P Abbeel, M Jordan, P Moritz
International conference on machine learning, 1889-1897, 2015
Optimal feedback control as a theory of motor coordination
E Todorov, MI Jordan
Nature neuroscience 5 (11), 1226-1235, 2002
An introduction to MCMC for machine learning
C Andrieu, N De Freitas, A Doucet, MI Jordan
Machine learning 50 (1-2), 5-43, 2003
On discriminative vs. generative classifiers: A comparison of logistic regression and naive bayes
A Ng, MI Jordan
Advances in Neural Information Processing Systems 14, 841, 2002
Kalman filtering with intermittent observations
B Sinopoli, L Schenato, M Franceschetti, K Poolla, MI Jordan, SS Sastry
IEEE transactions on Automatic Control 49 (9), 1453-1464, 2004
Learning in graphical models
MI Jordan
Springer Science & Business Media, 1998
Kernel independent component analysis
FR Bach, MI Jordan
Journal of machine learning research 3 (Jul), 1-48, 2002
Active learning with statistical models
DA Cohn, Z Ghahramani, MI Jordan
Journal of artificial intelligence research 4, 129-145, 1996
Machine learning: Trends, perspectives, and prospects
MI Jordan, TM Mitchell
Science 349 (6245), 255-260, 2015
Loopy belief propagation for approximate inference: An empirical study
K Murphy, Y Weiss, MI Jordan
arXiv preprint arXiv:1301.6725, 2013
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