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ICML
2004
IEEE
14 years 9 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 ...
ATAL
2010
Springer
13 years 9 months ago
History-dependent graphical multiagent models
A dynamic model of a multiagent system defines a probability distribution over possible system behaviors over time. Alternative representations for such models present tradeoffs i...
Quang Duong, Michael P. Wellman, Satinder P. Singh...
BMCBI
2010
138views more  BMCBI 2010»
13 years 8 months ago
Amino acid classification based spectrum kernel fusion for protein subnuclear localization
Background: Prediction of protein localization in subnuclear organelles is more challenging than general protein subcelluar localization. There are only three computational models...
Suyu Mei, Wang Fei
CORR
2007
Springer
109views Education» more  CORR 2007»
13 years 8 months ago
Optimal Causal Inference
We consider an information-theoretic objective function for statistical modeling of time series that embodies a parametrized trade-off between the predictive power of a model and...
Susanne Still, James P. Crutchfield, Christopher J...
KDD
2000
ACM
142views Data Mining» more  KDD 2000»
14 years 4 days ago
Automating exploratory data analysis for efficient data mining
Having access to large data sets for the purpose of predictive data mining does not guarantee good models, even when the size of the training data is virtually unlimited. Instead,...
Jonathan D. Becher, Pavel Berkhin, Edmund Freeman