4591 search results - page 552 / 919 » Learning from Dyadic Data |
146
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ICML
2005
IEEE
16 years 7 months ago
2005
IEEE
In this paper, we review the paradigm of inductive process modeling, which uses background knowledge about possible component processes to construct quantitative models of dynamic...
204
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ICML
1998
IEEE
16 years 7 months ago
1998
IEEE
Stochastic topological models, and hidden Markov models in particular, are a useful tool for robotic navigation and planning. In previous work we have shown how weak odometric dat...
141
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KDD
2005
ACM
16 years 7 months ago
2005
ACM
In several organizations, it has become increasingly popular to document and log the steps that makeup a typical business process. In some situations, a normative workflow model o...
183
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ECML
2007
Springer
16 years 27 days ago
2007
Springer
Boosting is a simple yet powerful modeling technique that is used in many machine learning and data mining related applications. In this paper, we propose a novel scale-space based...
161
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ICML
2010
IEEE
2010
IEEE
Unsupervised Risk Stratification in Clinical Datasets: Identifying Patients at Risk of Rare Outcomes
15 years 7 months ago
Most existing algorithms for clinical risk stratification rely on labeled training data. Collecting this data is challenging for clinical conditions where only a small percentage ...