Making Robots Smarter is a book about learning robots. It treats this topic based on the idea that the integration of sensing and action is the central issue. In the first part of the book, aspects of learning in execution and control are discussed. Methods for the automatic synthesis of controllers, for active sensing, for learning to enhance assembly, and for learning sensor-based navigation are presented. Since robots are not isolated but should serve us, the second part of the book discusses learning for human-robot interaction. Methods of learning understandable concepts for...
Making Robots Smarter is a book about learning robots. It treats this topic based on the idea that the integration of sensing and action is t...
Introduction The dramatic increase in available computer storage capacity over the last 10 years has led to the creation of very large databases of scienti?c and commercial information. The need to analyze these masses of data has led to the evolution of the new ?eld knowledge discovery in databases (KDD) at the intersection of machine learning, statistics and database technology. Being interdisciplinary by nature, the ?eld o?ers the opportunity to combine the expertise of di?erent ?elds intoacommonobjective.Moreover, withineach?elddiversemethodshave been developed and justi?ed with respect...
Introduction The dramatic increase in available computer storage capacity over the last 10 years has led to the creation of very large databases of sc...
Es wurde gezeigt, dass das Bootstrap-Problem bei der geometrischen Szenenrekonstruktion eine wichtige Rolle spielt und dass das Problem der physikalischen Korrespondenz als eine spezielle Sichtweise des Rekonstruktionsproblems gesehen werden kann. Weiterhin wurde ein wissensbasier ter Ansatz vorgestellt, um das Bootstrap-Problem zu umgehen. Literatur Bajcsy + Lieberman 76: Texture Gradient as a Depth Cue, R. Bajcsy und L.1. Lieberman, Computer Graphics and Image Processing 5, 52-67 (1976). Bartsch u.a. 86: Merkmalsdetektion in Farbbildern als Grundlage zur Korrespondenzanalyse in...
Es wurde gezeigt, dass das Bootstrap-Problem bei der geometrischen Szenenrekonstruktion eine wichtige Rolle spielt und dass das Problem der physikalis...
Die Autoren geben eine fundierte Einfuhrung in die Informatik, die von Anfang an die Zusammenhange zwischen den Teilgebieten des Faches betont. Das Buch ist kompakt, weil der gemeinsame Kern der verschiedenen Informatikgebiete betrachtet wird. In einer integrativen Sichtweise werden Modellierung, abstrakte Datentypen, Algorithmen sowie nebenlaufige und verteilte Programmierung behandelt. Die grundlegenden Konzepte der Informatik werden dabei mittels der Programmiersprache Java realisiert.
Wesentliches Anliegen der Autoren ist es, die Informatik als Wissenschaft der...
Die Autoren geben eine fundierte Einfuhrung in die Informatik, die von Anfang an die Zusammenhange zwischen den Teilgebieten des Faches betont. Das...
Making Robots Smarter is a book about learning robots. It treats this topic based on the idea that the integration of sensing and action is the central issue. In the first part of the book, aspects of learning in execution and control are discussed. Methods for the automatic synthesis of controllers, for active sensing, for learning to enhance assembly, and for learning sensor-based navigation are presented. Since robots are not isolated but should serve us, the second part of the book discusses learning for human-robot interaction. Methods of learning understandable concepts for...
Making Robots Smarter is a book about learning robots. It treats this topic based on the idea that the integration of sensing and action is t...
Thiscovers topics such as renewable energy supply, energy storage and e-mobility, efficiencyin data centers and networks, sustainable food and water supply, sustainablehealth, industrial production and quality, etc.
Thiscovers topics such as renewable energy supply, energy storage and e-mobility, efficiencyin data centers and networks, sustainable food and water s...
Katharina Morik J?rg Rahnenf?hrer Christian Wietfeld
Addresses novel machine learning algorithms that are challenged by high-throughput data, by high dimensions, or by complex structures of the data in three volumes. Resource constraints are given by the relation between the demands for processing the data and the capacity of the computing machinery. Comprehensive overview of novel approaches to machine learning research that consider resource constraints and application of the described methods.
Addresses novel machine learning algorithms that are challenged by high-throughput data, by high dimensions, or by complex structures of the data i...
Machine Learning under Resource Constraints addresses novel machine learning algorithms that are challenged by high-throughput data, by high dimensions, or by complex structures of the data in three volumes. Resource constraints are given by the relation between the demands for processing the data and the capacity of the computing machinery. The resources are runtime, memory, communication, and energy. Hence, modern computer architectures play a significant role. Novel machine learning algorithms are optimized with regard to minimal resource consumption. Moreover, learned predictions are...
Machine Learning under Resource Constraints addresses novel machine learning algorithms that are challenged by high-throughput data, by high dimension...
