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AAAI
1998
14 years 11 months ago
Structured Representation of Complex Stochastic Systems
This paperconsidersthe problem of representingcomplex systems that evolve stochastically over time. Dynamic Bayesian networks provide a compact representation for stochastic proce...
Nir Friedman, Daphne Koller, Avi Pfeffer
ACL
2007
14 years 11 months ago
A Bayesian Model for Discovering Typological Implications
A standard form of analysis for linguistic typology is the universal implication. These implications state facts about the range of extant languages, such as “if objects come af...
Hal Daumé III, Lyle Campbell
AUSAI
2006
Springer
15 years 1 months ago
Robust Character Recognition Using a Hierarchical Bayesian Network
There is increasing evidence to suggest that the neocortex of the mammalian brain does not consist of a collection of specialised and dedicated cortical architectures, but instead ...
John Thornton, Torbjorn Gustafsson, Michael Blumen...
ICML
2005
IEEE
15 years 10 months ago
Bayesian hierarchical clustering
We present a novel algorithm for agglomerative hierarchical clustering based on evaluating marginal likelihoods of a probabilistic model. This algorithm has several advantages ove...
Katherine A. Heller, Zoubin Ghahramani
97
Voted
IR
2002
14 years 9 months ago
Hierarchical Text Categorization Using Neural Networks
This paper presents the design and evaluation of a text categorization method based on the Hierarchical Mixture of Experts model. This model uses a divide and conquer principle to ...
Miguel E. Ruiz, Padmini Srinivasan