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Abstractions for Security Protocol Verification
(2015)We present a large class of security protocol abstractions with the aim of improving the scope and efficiency of verification tools. We propose typed abstractions, which transform a term's structure based on its type, and untyped abstractions, which remove atomic messages, variables, and redundant terms. Our theory improves on previous work by supporting a useful subclass of shallow subterm-convergent rewrite theories, user-defined types, ...Report -
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Archiv für Zeitgeschichte Jahresbericht 2014
(2015)Archiv für Zeitgeschichte JahresberichtReport -
Automatic problem-specific hyperparameter optimization and model selection for supervised machine learning: Technical Report
(2015)The use of machine learning techniques has become increasingly widespread in commercial applications and academic research. Machine learning algorithms learn a model from data that allows computers to make and improve predictions or behaviors. Despite their popularity and usefulness, most machine learning techniques require expert knowledge to guide the decisions about the most appropriate model and settings for a particular problem. In ...Report -