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UM
2005
Springer
15 years 7 months ago
Data-Driven Refinement of a Probabilistic Model of User Affect
We present further developments in our work on using data from real users to build a probabilistic model of user affect based on Dynamic Bayesian Networks (DBNs) and designed to de...
Cristina Conati, Heather Maclaren
DSS
2007
127views more  DSS 2007»
15 years 1 months ago
Large-scale regulatory network analysis from microarray data: modified Bayesian network learning and association rule mining
We present two algorithms for learning large-scale gene regulatory networks from microarray data: a modified informationtheory-based Bayesian network algorithm and a modified asso...
Zan Huang, Jiexun Li, Hua Su, George S. Watts, Hsi...
UAI
2001
15 years 2 months ago
Exact Inference in Networks with Discrete Children of Continuous Parents
Many real life domains contain a mixture of discrete and continuous variables and can be modeled as hybrid Bayesian Networks (BNs). An important subclass of hybrid BNs are conditi...
Uri Lerner, Eran Segal, Daphne Koller
GECCO
2006
Springer
165views Optimization» more  GECCO 2006»
15 years 5 months ago
Comparing mathematical models on the problem of network inference
In this paper we address the problem of finding gene regulatory networks from experimental DNA microarray data. We focus on the evaluation of the performance of different mathemat...
Christian Spieth, Nadine Hassis, Felix Streichert
JMLR
2010
134views more  JMLR 2010»
14 years 8 months ago
Inference of Graphical Causal Models: Representing the Meaningful Information of Probability Distributions
This paper studies the feasibility and interpretation of learning the causal structure from observational data with the principles behind the Kolmogorov Minimal Sufficient Statist...
Jan Lemeire, Kris Steenhaut