When creating a visual recognition system for a novel task, one of the main burdens is the collection and annotation of data. Often several thousand samples need to be manually reviewed and labeled so that the recognition system achieves the desired accuracy. The goal of this thesis is to provide methods that lower the annotation effort for visual scene and object recognition. These methods are applicable to traditional pattern recognition approaches as well as methods from the field of deep ...

In this manuscript we develop and apply modern algorithmic data reduction techniques to tackle scalability issues and enable statistical data analysis of massive data sets. Our algorithms follow a general scheme, where a reduction technique is applied to the large-scale data to obtain a small summary of sublinear size to which a classical algorithm is applied. The techniques for obtaining these summaries depend on the problem that we want to solve. The size of the summaries is usually paramet...

This thesis is dedicated to string processing algorithms and to combinatorics on words. With respect to the former, we devise Lempel-Ziv (LZ) factorization and sparse suffix sorting algorithms. With respect to the latter, we search for all distinct squares, all maximal α-gapped repeats, and all maximal α-gapped palindromes. The topics of the presented approaches are related: for instance, our results for the LZ factorization have applications for finding all distinct squares, whereas our spar...

Markov decision processes model stochastic uncertainty in systems and allow one to construct strategies which optimize the behaviour of a system with respect to some reward function. However, the parameters for this uncertainty, that is, the probabilities inside a Markov decision model, are derived from empirical or expert knowledge and are themselves subject to uncertainties such as measurement errors or limited expertise. This work considers second-order uncertainty models for Markov decisi...

In recent years, statistical machine learning has emerged as a key technique for tackling problems that elude a classic algorithmic approach. One such problem, with a major impact on human life, is the analysis of complex biomedical data. Solving this problem in a fast and efficient manner is of major importance, as it enables, e.g., the prediction of the efficacy of different drugs for therapy selection. While achieving the highest possible prediction quality appears desirable, doing so is o...

The quest for more performance of applications and systems became more challenging in the recent years. Especially in the cyber-physical and mobile domain, the performance requirements increased significantly. Applications, previously found in the high-performance domain, emerge in the area of resource-constrained domain. Modern heterogeneous high-performance MPSoCs provide a solid foundation to satisfy the high demand. Such systems combine general processors with specialized accelerators ran...

This work is about the estimation of exponential family models on resource-constrained systems. Our main goal is learning probabilistic models on devices with highly restricted storage, arithmetic, and computational capabilities—so called, ultra-low-power devices. Enhancing the learning capabilities of such devices opens up opportunities for intelligent ubiquitous systems in all areas of life, from medicine, over robotics, to home automation—to mention just a few. We investigate the inhe...

Technological advances in the music industry have dramatically changed how people access and listen to music. Today, online music stores and streaming services offer easy and immediate means to buy or listen to a huge number of songs. One traditional way to find interesting items in such cases when a vast amount of choices are available is to ask others for recommendations. Music providers utilize correspondingly music recommender systems as a software solution to the problem of music overloa...

In the modern world, we are increasingly surrounded by computation devices with communication links and one or more microphones. Such devices are, for example, smartphones, tablets, laptops or hearing aids. These devices can work together as nodes in an acoustic sensor network (ASN). Such networks are a growing platform that opens the possibility for many practical applications. ASN based speech enhancement, source localization, and event detection can be applied for teleconferencing, camer...

Eine der revolutionären Veränderungen des 20. und 21. Jahrhunderts der Menschheit ist die Computerisierung und Digitalisierung der Welt. Tagtäglich werden große Menge von Daten erzeugt. Es ist unmöglich für uns Menschen, ohne anspruchsvolle Verfahren und Algorithmen, aus diesen enorm großen Datenmengen versteckte Strukturen (Wissen) herauszufiltern. Datamining, Machine Learning und Pattern Recognition sind ähnliche Disziplinen, mit denen man versuchen will, diese Herausforderung zu bewältige...

The Steiner tree problem (STP) is a central and well-studied graph-theoretical combinatorial optimization problem which plays an important role in various applications. It can be stated as follows: Given a weighted graph and a set of terminal vertices, find a subset of edges which connects the terminals at minimum cost. However, in real-world applications the input data might not be given with certainty or it might depend on future decisions. For the STP, for example, edge costs representing ...

During the past decades numerous spectrometry devices, e.g. mass spectrometry or liquid or gas chromatography, have been engineered to measure the different properties of molecules, compounds or even complex structures. One device exploits the different mobilities of ionized analytes, the so-called ion mobility spectrometer. The advantages of this device are the low costs of production and maintenance (e.g. a high vacuum as in mass spectrometry is not required), the fast capture (a few millis...

Bei der Entwicklung und Nutzung von eingebetteten Systemen werden häufig Energiemodelle der einzelnen Systemkomponenten benötigt, um den Energiebedarf des Gesamtsystems abschätzen zu können. Die Erstellung und Verfeinerung solcher Modelle bedeutet meist aufwändige Handarbeit, da die notwendigen Mess- und Auswertungsschritte von den jeweiligen Komponenten abhängen. Diese Arbeit zeigt, dass es trotz der Unterschiede zwischen verschiedenen Peripheriegeräten möglich ist, mit einem generische...

Kontextfreie Spiele sind ein formales Modell, welches in seiner einfachsten Form den Ableitungsmechanismus kontextfreier Grammatiken zu einem Spiel für zwei Spieler (genannt Juliet und Romeo) verallgemeinert; dabei wählt in einer gegebenen Satzform (d.h. einer Zeichenkette aus Terminal- und Nichtterminalsymbolen) jeweils Juliet ein zu ersetzendes Nichtterminalsymbol aus, worauf Romeo jeweils entsprechend den Ableitungsregeln entscheidet, wodurch dieses Nichtterminalsymbol ersetzt werden soll....

Gegenstand dieser Arbeit sind algorithmische Methoden der modernen Datenanalyse. Dabei werden vorwiegend zwei übergeordnete Themen behandelt: Datenstromalgorithmen mit Kompressionseigenschaften und Approximationsalgorithmen für Clusteringverfahren. Datenstromalgorithmen verarbeiten einen Datensatz sequentiell und haben das Ziel, Eigenschaften des Datensatzes (approximativ) zu bestimmen, ohne dabei den gesamten Datensatz abzuspeichern. Unter Clustering versteht man die Partitionierung eines Da...

In our article Session-based item recommendation in e-commerce: on short-term intents, reminders, trends and discounts accepted for publication in User Modeling and User-Adapted Interaction (UMUAI) we examined a classification-based approach to analyze what makes a recommendation successful. In the process we generated over 95 features for each single recommendation action in our data set provided by the online fashion retailer Zalando. Due to space issues we could only explain some of the mo...

Spreadsheets are interactive data organization and calculation programs that are developed in spreadsheet environments like Microsoft Excel or LibreOffice Calc. They are probably the most successful example of end-user developed software and are utilized in almost all branches and at all levels of companies. Although spreadsheets often support important decision making processes, they are, like all software, prone to error. In several cases, faults in spreadsheets have caused severe losses of...

Software is so prevalent in all areas of life that one could expect we have come up with more simple and intuitive ways for its creation by now. However, software development is still too complicated to easily and efficiently cope with individual demands, customizations, and changes. Model-based approaches promise improvements through a more comprehensible layer of abstraction, but they are rarely fully embraced in practice. They are perceived as being overly complex, imposing additional work...