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JACM
2010
208views more  JACM 2010»
13 years 5 months ago
The nested chinese restaurant process and bayesian nonparametric inference of topic hierarchies
clustering of documents according to sharing of topics at multiple levels of abstraction. Given a corpus of documents, a posterior inference algorithm finds an approximation to a ...
David M. Blei, Thomas L. Griffiths, Michael I. Jor...
IPSN
2004
Springer
14 years 23 days ago
A probabilistic approach to inference with limited information in sensor networks
We present a methodology for a sensor network to answer queries with limited and stochastic information using probabilistic techniques. This capability is useful in that it allows...
Rahul Biswas, Sebastian Thrun, Leonidas J. Guibas
NIPS
1998
13 years 8 months ago
Learning Nonlinear Dynamical Systems Using an EM Algorithm
The Expectation Maximization EM algorithm is an iterative procedure for maximum likelihood parameter estimation from data sets with missing or hidden variables 2 . It has been app...
Zoubin Ghahramani, Sam T. Roweis
OSDI
2008
ACM
14 years 7 months ago
Probabilistic Inference in Queueing Networks
Although queueing models have long been used to model the performance of computer systems, they are out of favor with practitioners, because they have a reputation for requiring u...
Charles A. Sutton, Michael I. Jordan
JOI
2007
56views more  JOI 2007»
13 years 7 months ago
Hirsch's h-index: A stochastic model
We propose a simple stochastic model for an author’s production/citation process in order to investigate the recently proposed hindex for measuring an author’s research output...
Quentin L. Burrell