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ICML
2004
IEEE
16 years 3 months ago
Dynamic conditional random fields: factorized probabilistic models for labeling and segmenting sequence data
In sequence modeling, we often wish to represent complex interaction between labels, such as when performing multiple, cascaded labeling tasks on the same sequence, or when longra...
Charles A. Sutton, Khashayar Rohanimanesh, Andrew ...
AI
2006
Springer
15 years 6 months ago
Modeling Causal Reinforcement and Undermining with Noisy-AND Trees
Abstract. Causal modeling, such as noisy-OR, reduces probability parameters to be acquired in constructing a Bayesian network. Multiple causes can reinforce each other in producing...
Y. Xiang, N. Jia
BMCBI
2007
197views more  BMCBI 2007»
15 years 2 months ago
Boolean networks using the chi-square test for inferring large-scale gene regulatory networks
Background: Boolean network (BN) modeling is a commonly used method for constructing gene regulatory networks from time series microarray data. However, its major drawback is that...
Haseong Kim, Jae K. Lee, Taesung Park
HUC
2007
Springer
15 years 8 months ago
A Statistical Reasoning System for Medication Prompting
We describe our experience building and using a reasoning system for providing context-based prompts to elders to take their medication. We describe the process of specification, ...
Sengul Vurgun, Matthai Philipose, Misha Pavel
139
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ICMCS
2005
IEEE
102views Multimedia» more  ICMCS 2005»
15 years 8 months ago
A Probabilistic Framework for TV-News Stories Detection and Classification
In this paper we face the problem of partitioning the news videos into stories, and of their classification according to a predefined set of categories. In particular, we propose ...
Francesco Colace, Pasquale Foggia, Gennaro Percann...