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Article
Open AccessHandling hybrid and missing data in constraint-based causal discovery to study the etiology of ADHD
Causal discovery is an increasingly important method for data analysis in the field of medical research. In this paper, we consider two challenges in causal discovery that occur very often when working with me...
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Chapter and Conference Paper
Copula PC Algorithm for Causal Discovery from Mixed Data
We propose the ‘Copula PC’ algorithm for causal discovery from a combination of continuous and discrete data, assumed to be drawn from a Gaussian copula model. It is based on a two-step approach. The first ste...
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Article
A quantitative analysis of the robustness of knowledge-based systems through degradation studies
The overall aim of this paper is to provide a general setting for quantitative quality measures of knowledge-based system behaviour that is widely applicable to many knowledge-based systems. We propose a gener...
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Chapter and Conference Paper
Scalable Instance Retrieval for the Semantic Web by Approximation
Approximation has been identified as a potential way of reducing the complexity of logical reasoning. Here we explore approximation for speeding up instance retrieval in a Semantic Web context. For OWL ontolog...
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Chapter and Conference Paper
Approximating Description Logic Classification for Semantic Web Reasoning
In many application scenarios, the use of the Web ontology language OWL is hampered by the complexity of the underlying logic that makes reasoning in OWL intractable in the worst case. In this paper, we addres...