Titlebook: Machine Learning and Knowledge Extraction; 4th IFIP TC 5, TC 12 Andreas Holzinger,Peter Kieseberg,Edgar Weippl Conference proceedings 2020

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植物學(xué)

Explainable Artificial Intelligence: Concepts, Applications, Research Challenges and Visions,y concerns, like the European Union General Data Protection Regulation, which sets standards for the production of explanations from automated or semi-automated decision making. Despite the fact that all this research activity is the growing acknowledgement that the topic of explainability is essent

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The Explanation Game: Explaining Machine Learning Models Using Shapley Values,htforward confidence intervals on their attributions. Furthermore, it allows us to interpret the attributions as . of an input relative to a distribution of reference inputs. We tie this idea to classic research in cognitive psychology on contrastive explanations, and propose a conceptual framework

殺菌劑

Explain Graph Neural Networks to Understand Weighted Graph Features in Node Classification,ne to identify the critical factors used for node classification. We use four datasets (two synthetic and two real) to validate our methods. Our results demonstrate that our explanation approach can mimic data patterns used for node classification by human interpretation and disentangle different fe

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演講

A Projected Stochastic Gradient Algorithm for Estimating Shapley Value Applied in Attribute Importair theoretical guarantees, they are however really hard to calculate. Indeed, the complexity increases exponentially with the dimension (the number of variables). In this article, we propose two novel methods to approximate these Shapley Values. The first one is an optimization of an already existin

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擁護(hù)

Cooperation Between Data Analysts and Medical Experts: A Case Study,om the medical expert because of the correct interpretation of the medical data and its resulting associations. On the other hand, it requires a proper understanding of the task from the data analyst’s point of view, a lot of iterations of graphs, and other models, which must be modified to be easy

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The European Legal Framework for Medical AI,duct approval procedures and liability law. This analysis of the current state of law, including its problems and ambiguities regarding AI, is complemented by an outlook at the proposed amendments to product approval procedures and liability law, which, by endorsing a human-centric approach, will fu