Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 12 of 12 for “"Maschinelles Lernen"”.
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Programming abstractions, compilation, and execution techniques for massively parallel data analysis
… Algorithmen aus den Bereichen Data Mining und Maschinelles Lernen hinzu, um versteckte Muster in den Daten zu erkennen, oder Vorhersagemodelle zu trainieren. Mit zunehmender Datenmenge und Komplexität der Analysen wird jedoch eine neue Generation von Systemen benötigt, die diese Kombination aus …
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Quantifying Dislocation Microstructures
In this work, we reconstructed and full characterized a dislocation microstructure that formed during an in situ micro-cantilever beam experiment. Based on this information, we were then able to infer how the dislocations propagated from the notch into the specimen. We propose using the so-called …
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Behavior-specific proprioception models for robotic force estimation
Robots that support humans in physically demanding tasks require accurate force sensing capabilities. A common way to achieve this is by monitoring the interaction with the environment directly with dedicated force sensors. Major drawbacks of such special purpose sensors are the increased costs and …
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Prediction with Mixture Models
Learning a model for the relationship between the attributes and the annotated labels of data examples serves two purposes. Firstly, it enables the prediction of the label for examples without annotation. Secondly, the parameters of the model can provide useful insights into the structure of the …
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Discriminative Classification Models for Internet Security
Services that operate over the Internet are under constant threat of being exposed to fraudulent use. Maintaining good user experience for legitimate users often requires the classification of entities as malicious or legitimate in order to initiate countermeasures. As an example, inbound email …
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Learning under differing training and test distributions
One of the main problems in machine learning is to train a predictive model from training data and to make predictions on test data. Most predictive models are constructed under the assumption that the training data is governed by the exact same distribution which the model will later be exposed …
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Active evaluation of predictive models
The field of machine learning studies algorithms that infer predictive models from data. Predictive models are applicable for many practical tasks such as spam filtering, face and handwritten digit recognition, and personalized product recommendation. In general, they are used to predict a target …
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Prediction games : machine learning in the presence of an adversary
In many applications one is faced with the problem of inferring some functional relation between input and output variables from given data. Consider, for instance, the task of email spam filtering where one seeks to find a model which automatically assigns new, previously unseen emails to class …
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Analyse von Translationsstarts in prokaryotischen Genomen mit Methoden des Maschinellen Lernens
… zwei Verfahren aus dem Bereich des Maschinellen Lernens zur Verbesserung der Annotation prokaryotischer Genome, vorgestellt: Der Oligo-Kern-Algorithmus, ein überwachtes Verfahren zur Analyse von Signalen in biologischen Sequenzen und TICO (Translation Initiation site COrrection), ein Programm zur …