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Komponisten in Bayern. Band 63: Klaus Obermayer
Klaus Obermayer war ein »Musikmensch der vielen Talente«. Als Musikpädagoge hat er zahlreiche junge Menschen für Musik begeistert, als Musikpolitiker kämpfte er dafür, dass Musik keine brotlose Kunst ist, als Musikjournalist trat er wortgewaltig für seine Kunst ein, als Verleger erkundete er, lange bevor Self-Publishing zu einem Trend wurde, die Möglichkeiten, direkt als Komponist seine »Kunden« zu finden und die daraus gewonnenen Erfahrungen für die Kollegen zu nutzen. Doch im Zentrum standen für ihn das eigene Spielen und Konzertieren, dem er sich als Spätberufener auf dem Fagott zuwandte, und vor allem das Komponieren: Sein Werk zeugt von einer erstaunlichen Produktivität un...
Self-organizing Map Formation
This book provides an overview of self-organizing map formation, including recent developments. Self-organizing maps form a branch of unsupervised learning, which is the study of what can be determined about the statistical properties of input data without explicit feedback from a teacher. The articles are drawn from the journal Neural Computation.The book consists of five sections. The first section looks at attempts to model the organization of cortical maps and at the theory and applications of the related artificial neural network algorithms. The second section analyzes topographic maps and their formation via objective functions. The third section discusses cortical maps of stimulus fea...
Prerational Intelligence
The focus of prerational intelligence is on the way animals and artificial systems utilize information about their surroundings in order to behave intelligently; the premise is that logic and symbolic reasoning are neither necessary nor, possibly, sufficient. Experts in the fields of biology, psychology, robotics, AI, mathematics, engineering, computer science, and philosophy review the evidence that intelligent behaviour can arise in systems of simple agents interacting according to simple rules; that self-organization and interaction with the environment are critical; and that quick approximations may replace logical analyses. It is argued that a better understanding of the intelligence inherent in procedure like those illustrated will eventually shed light on how rational intelligence is realised in humans. Readership: Scientifically literate general readers and scientists in all fields interested in understanding and duplicating biological intelligence.
Regularization, Optimization, Kernels, and Support Vector Machines
Regularization, Optimization, Kernels, and Support Vector Machines offers a snapshot of the current state of the art of large-scale machine learning, providing a single multidisciplinary source for the latest research and advances in regularization, sparsity, compressed sensing, convex and large-scale optimization, kernel methods, and support vector machines. Consisting of 21 chapters authored by leading researchers in machine learning, this comprehensive reference: Covers the relationship between support vector machines (SVMs) and the Lasso Discusses multi-layer SVMs Explores nonparametric feature selection, basis pursuit methods, and robust compressive sensing Describes graph-based regular...
Learning to Rank for Information Retrieval and Natural Language Processing
Learning to rank refers to machine learning techniques for training the model in a ranking task. Learning to rank is useful for many applications in information retrieval, natural language processing, and data mining. Intensive studies have been conducted on the problem recently and significant progress has been made. This lecture gives an introduction to the area including the fundamental problems, existing approaches, theories, applications, and future work. The author begins by showing that various ranking problems in information retrieval and natural language processing can be formalized as two basic ranking tasks, namely ranking creation (or simply ranking) and ranking aggregation. In r...
Prerational Intelligence: Adaptive Behavior and Intelligent Systems Without Symbols and Logic , Volume 1, Volume 2 Prerational Intelligence: Interdisciplinary Perspectives on the Behavior of Natural and Artificial Systems, Volume 3
The present book is the product of conferences held in Bielefeld at the Center for interdisciplinary Sturlies (ZiF) in connection with a year-long ZiF Research Group with the theme "Prerational intelligence". The premise ex plored by the research group is that traditional notions of intelligent behav ior, which form the basis for much work in artificial intelligence and cog nitive science, presuppose many basic capabilities which are not trivial, as more recent work in robotics and neuroscience has shown, and that these capabilities may be best understood as ernerging from interaction and coop eration in systems of simple agents, elements that accept inputs from and act upon their surroundin...
Learning to Rank for Information Retrieval and Natural Language Processing, Second Edition
Learning to rank refers to machine learning techniques for training a model in a ranking task. Learning to rank is useful for many applications in information retrieval, natural language processing, and data mining. Intensive studies have been conducted on its problems recently, and significant progress has been made. This lecture gives an introduction to the area including the fundamental problems, major approaches, theories, applications, and future work. The author begins by showing that various ranking problems in information retrieval and natural language processing can be formalized as two basic ranking tasks, namely ranking creation (or simply ranking) and ranking aggregation. In rank...
Advances in Neural Information Processing Systems 17
Papers presented at NIPS, the flagship meeting on neural computation, held in December 2004 in Vancouver.The annual Neural Information Processing Systems (NIPS) conference is the flagship meeting on neural computation. It draws a diverse group of attendees--physicists, neuroscientists, mathematicians, statisticians, and computer scientists. The presentations are interdisciplinary, with contributions in algorithms, learning theory, cognitive science, neuroscience, brain imaging, vision, speech and signal processing, reinforcement learning and control, emerging technologies, and applications. Only twenty-five percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. This volume contains the papers presented at the December, 2004 conference, held in Vancouver.
Advances in Neural Information Processing Systems 11
The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. It draws preeminent academic researchers from around the world and is widely considered to be a showcase conference for new developments in network algorithms and architectures. The broad range of interdisciplinary research areas represented includes computer science, neuroscience, statistics, physics, cognitive science, and many branches of engineering, including signal processing and control theory. Only about 30 percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. These proceedings contain all of the papers that were presented.
Research Handbook on Big Data Law
This state-of-the-art Research Handbook provides an overview of research into, and the scope of current thinking in, the field of big data analytics and the law. It contains a wealth of information to survey the issues surrounding big data analytics in legal settings, as well as legal issues concerning the application of big data techniques in different domains.
