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» Learning a Hidden Hypergraph
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94
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IUI
2004
ACM
15 years 6 months ago
Sheepdog: learning procedures for technical support
Technical support procedures are typically very complex. Users often have trouble following printed instructions describing how to perform these procedures, and these instructions...
Tessa A. Lau, Lawrence D. Bergman, Vittorio Castel...
110
Voted
NIPS
1998
15 years 2 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
105
Voted
ESWA
2006
103views more  ESWA 2006»
15 years 23 days ago
Model gene network by semi-fixed Bayesian network
Gene networks describe functional pathways in a given cell or tissue, representing processes such as metabolism, gene expression regulation, and protein or RNA transport. Thus, le...
Tie-Fei Liu, Wing-Kin Sung, Ankush Mittal
118
Voted
ECML
2004
Springer
15 years 6 months ago
Fisher Kernels for Logical Sequences
One approach to improve the accuracy of classifications based on generative models is to combine them with successful discriminative algorithms. Fisher kernels were developed to c...
Kristian Kersting, Thomas Gärtner
107
Voted
ICML
2008
IEEE
16 years 1 months ago
Efficiently learning linear-linear exponential family predictive representations of state
Exponential Family PSR (EFPSR) models capture stochastic dynamical systems by representing state as the parameters of an exponential family distribution over a shortterm window of...
David Wingate, Satinder P. Singh