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» Exploiting Data Missingness in Bayesian Network Modeling
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IJCAI
2003
15 years 13 days ago
Dynamic Bayesian modeling of the cerebral activity
Conventional methods used for the interpretation of activation data provided by functional neuroimaging techniques provide useful insights on what the networks of cerebral structu...
Vincent Labatut, Josette Pastor, Serge Ruff
FLAIRS
2006
15 years 14 days ago
Decomposing Local Probability Distributions in Bayesian Networks for Improved Inference and Parameter Learning
A major difficulty in building Bayesian network models is the size of conditional probability tables, which grow exponentially in the number of parents. One way of dealing with th...
Adam Zagorecki, Mark Voortman, Marek J. Druzdzel
WWW
2008
ACM
15 years 11 months ago
Computable social patterns from sparse sensor data
We present a computational framework to automatically discover high-order temporal social patterns from very noisy and sparse location data. We introduce the concept of social foo...
Dinh Q. Phung, Brett Adams, Svetha Venkatesh
AIED
2007
Springer
15 years 5 months ago
Relating Machine Estimates of Students' Learning Goals to Learning Outcomes: A DBN Approach
Students’ actions while working with a tuoring system were used to generate estimates of learning goals, specifically, the goal of learning by using multimedia help resources, an...
Carole R. Beal, Lei Qu
KDD
1998
ACM
442views Data Mining» more  KDD 1998»
15 years 3 months ago
BAYDA: Software for Bayesian Classification and Feature Selection
BAYDA is a software package for flexible data analysis in predictive data mining tasks. The mathematical model underlying the program is based on a simple Bayesian network, the Na...
Petri Kontkanen, Petri Myllymäki, Tomi Siland...