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NIPS
1992
14 years 11 months ago
Hidden Markov Model} Induction by Bayesian Model Merging
This paper describes a technique for learning both the number of states and the topologyof Hidden Markov Models from examples. The inductionprocess starts with the most specific m...
Andreas Stolcke, Stephen M. Omohundro
ICASSP
2010
IEEE
14 years 10 months ago
Discriminative training methods for language models using conditional entropy criteria
This paper addresses the problem of discriminative training of language models that does not require any transcribed acoustic data. We propose to minimize the conditional entropy ...
Jui-Ting Huang, Xiao Li, Alex Acero
ALGORITHMICA
2010
95views more  ALGORITHMICA 2010»
14 years 10 months ago
Homogeneous String Segmentation using Trees and Weighted Independent Sets
We divide a string into k segments, each with only one sort of symbols, so as to minimize the total number of exceptions. Motivations come from machine learning and data mining. F...
Peter Damaschke
AUTOMATICA
2006
81views more  AUTOMATICA 2006»
14 years 10 months ago
An energy-gain bounding approach to robust fuzzy identification
A novel method for the robust identification of interpretable fuzzy models, based on the criterion that identification errors are least sensitive to data uncertainties and modelli...
Mohit Kumar, Norbert Stoll, Regina Stoll
CSDA
2007
142views more  CSDA 2007»
14 years 9 months ago
DIVCLUS-T: A monothetic divisive hierarchical clustering method
DIVCLUS-T is a divisive hierarchical clustering algorithm based on a monothetic bipartitional approach allowing the dendrogram of the hierarchy to be read as a decision tree. It i...
Marie Chavent, Yves Lechevallier, Olivier Briant