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Computational Learning Theory
This volume presents the proceedings of the Second European Conference on Computational Learning Theory (EuroCOLT '95), held in Barcelona, Spain in March 1995. The book contains full versions of the 28 papers accepted for presentation at the conference as well as three invited papers. All relevant topics in fundamental studies of computational aspects of artificial and natural learning systems and machine learning are covered; in particular artificial and biological neural networks, genetic and evolutionary algorithms, robotics, pattern recognition, inductive logic programming, decision theory, Bayesian/MDL estimation, statistical physics, and cryptography are addressed.
Learning Theory
This book constitutes the refereed proceedings of the 18th Annual Conference on Learning Theory, COLT 2005, held in Bertinoro, Italy in June 2005. The 45 revised full papers together with three articles on open problems presented were carefully reviewed and selected from a total of 120 submissions. The papers are organized in topical sections on: learning to rank, boosting, unlabeled data, multiclass classification, online learning, support vector machines, kernels and embeddings, inductive inference, unsupervised learning, generalization bounds, query learning, attribute efficiency, compression schemes, economics and game theory, separation results for learning models, and survey and prospects on open problems.
Algorithmic Learning Theory
This volume contains the papers presented at the 13th Annual Conference on Algorithmic Learning Theory (ALT 2002), which was held in Lub ̈ eck (Germany) during November 24–26, 2002. The main objective of the conference was to p- vide an interdisciplinary forum discussing the theoretical foundations of machine learning as well as their relevance to practical applications. The conference was colocated with the Fifth International Conference on Discovery Science (DS 2002). The volume includes 26 technical contributions which were selected by the program committee from 49 submissions. It also contains the ALT 2002 invited talks presented by Susumu Hayashi (Kobe University, Japan) on “Mathem...
Probability
Approximation of Large-Scale Dynamical Systems
The Oxford Handbook of Critical Concepts in Music Theory
Music Theory operates with a number of fundamental terms that are rarely explored in detail. This book offers in-depth reflections on key concepts from a range of philosophical and critical approaches that reflect the diversity of the contemporary music theory landscape.
Learning Theory and Kernel Machines
This book constitutes the joint refereed proceedings of the 16th Annual Conference on Computational Learning Theory, COLT 2003, and the 7th Kernel Workshop, Kernel 2003, held in Washington, DC in August 2003. The 47 revised full papers presented together with 5 invited contributions and 8 open problem statements were carefully reviewed and selected from 92 submissions. The papers are organized in topical sections on kernel machines, statistical learning theory, online learning, other approaches, and inductive inference learning.
Introduction to Computer and Network Security
Guides Students in Understanding the Interactions between Computing/Networking Technologies and Security Issues Taking an interactive, "learn-by-doing" approach to teaching, Introduction to Computer and Network Security: Navigating Shades of Gray gives you a clear course to teach the technical issues related to security. Unlike most computer security books, which concentrate on software design and implementation, cryptographic tools, or networking issues, this text also explores how the interactions between hardware, software, and users affect system security. The book presents basic principles and concepts, along with examples of current threats to illustrate how the principles can either e...
Computational Learning Theory
This book constitutes the refereed proceedings of the 4th European Conference on Computational Learning Theory, EuroCOLT'99, held in Nordkirchen, Germany in March 1999. The 21 revised full papers presented were selected from a total of 35 submissions; also included are two invited contributions. The book is divided in topical sections on learning from queries and counterexamples, reinforcement learning, online learning and export advice, teaching and learning, inductive inference, and statistical theory of learning and pattern recognition.
Pattern Recognition and String Matching
The research and development of pattern recognition have proven to be of importance in science, technology, and human activity. Many useful concepts and tools from different disciplines have been employed in pattern recognition. Among them is string matching, which receives much theoretical and practical attention. String matching is also an important topic in combinatorial optimization. This book is devoted to recent advances in pattern recognition and string matching. It consists of twenty eight chapters written by different authors, addressing a broad range of topics such as those from classifica tion, matching, mining, feature selection, and applications. Each chapter is self-contained, ...
Computational Graph Theory
One ofthe most important aspects in research fields where mathematics is "applied is the construction of a formal model of a real system. As for structural relations, graphs have turned out to provide the most appropriate tool for setting up the mathematical model. This is certainly one of the reasons for the rapid expansion in graph theory during the last decades. Furthermore, in recent years it also became clear that the two disciplines of graph theory and computer science have very much in common, and that each one has been capable of assisting significantly in the development of the other. On one hand, graph theorists have found that many of their problems can be solved by the use of com...
