11 Result(s)
within
Chapter
Perry Groot
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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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Chapter and Conference Paper
Causal Discovery from Medical Data: Dealing with Missing Values and a Mixture of Discrete and Continuous Data
Causal discovery is an increasingly popular 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 medic...
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Chapter and Conference Paper
Causal Discovery from Databases with Discrete and Continuous Variables
Bayesian Constraint-based Causal Discovery (BCCD) is a state-of-the-art method for robust causal discovery in the presence of latent variables. It combines probabilistic estimation of Bayesian networks over su...
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Chapter
Adaptive Control Strategies for Productive Toner Printers
This chapter discusses design considerations for industrial systems and processes when embedded systems allow to intelligently influence the system in real-time. It is shown that in such embedded systems the c...
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Chapter and Conference Paper
Learning from Multiple Annotators with Gaussian Processes
In many supervised learning tasks it can be costly or infeasible to obtain objective, reliable labels. We may, however, be able to obtain a large number of subjective, possibly noisy, labels from multiple anno...
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Chapter and Conference Paper
Combining Task Execution and Background Knowledge for the Verification of Medical Guidelines
The use of a medical guideline can be seen as the execution of computational tasks, sequentially or in parallel, in the face of patient data. It has been shown that many of such guidelines can be represented a...
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Chapter and Conference Paper
The Role of Model Checking in Critiquing Based on Clinical Guidelines
Medical critiquing systems criticise clinical actions performed by a physician. In order to provide useful feedback, an important task is to find differences between the actual actions and a set of ‘ideal’ act...
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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...
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Chapter and Conference Paper
Torture Tests: A Quantitative Analysis for the Robustness of Knowledge-Based Systems
The overall aim of this paper is to provide a general setting for quantitative quality measures of Knowledge-Based System behavior which is widely applicable to many Knowledge-Based Systems. We propose a gener...
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Chapter and Conference Paper
Formally Verifying Dynamic Properties of Knowledge Based Systems
In this paper we study dynamic properties of knowledge-based systems. We argue the importance of such dynamic properties for the construction and analysis of knowledge-based systems. We present a case-study of...
