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Computational Complexity and Statistical Physics
Computer science and physics have been closely linked since the birth of modern computing. In recent years, an interdisciplinary area has blossomed at the junction of these fields, connecting insights from statistical physics with basic computational challenges. Researchers have successfully applied techniques from the study of phase transitions to analyze NP-complete problems such as satisfiability and graph coloring. This is leading to a new understanding of the structure of these problems, and of how algorithms perform on them. Computational Complexity and Statistical Physics will serve as a standard reference and pedagogical aid to statistical physics methods in computer science, with a particular focus on phase transitions in combinatorial problems. Addressed to a broad range of readers, the book includes substantial background material along with current research by leading computer scientists, mathematicians, and physicists. It will prepare students and researchers from all of these fields to contribute to this exciting area.
Mathematical Foundations of Computer Science 2001
This book constitutes the refereed proceedings of the 26th International Symposium on Mathematical Foundations of Computer Science, MFCS 2001, held in Marianske Lazne, Czech Republic in August 2001. The 51 revised full papers presented together with 10 invited contributions were carefully reviewed and selected from a total of 118 submissions. All current aspects of theoretical computer science are addressed ranging from mathematical logic and programming theory to algorithms, discrete mathematics, and complexity theory. Besides classical issues, modern topics like quantum computing are discussed as well.
Machine Learning for Asset Management and Pricing
This textbook covers the latest advances in machine learning methods for asset management and asset pricing. Recent research in deep learning applied to finance shows that some of the (usually confidential) techniques used by asset managers result in better investments than the more standard techniques. Cutting-edge material is integrated with mainstream finance theory and statistical methods to provide a coherent narrative. Coverage includes an original machine learning method for strategic asset allocation; the no-arbitrage theory applied to a wide portfolio of assets as well as other asset management methods, such as mean-variance, Bayesian methods, linear factor models, and strategic ass...
The Nature of Computation
Computational complexity is one of the most beautiful fields of modern mathematics, and it is increasingly relevant to other sciences ranging from physics to biology. But this beauty is often buried underneath layers of unnecessary formalism, and exciting recent results like interactive proofs, phase transitions, and quantum computing are usually considered too advanced for the typical student. This book bridges these gaps by explaining the deep ideas of theoretical computer science in a clear and enjoyable fashion, making them accessible to non-computer scientists and to computer scientists who finally want to appreciate their field from a new point of view. The authors start with a lucid a...
Foundations of Intelligent Systems
This book constitutes the proceedings of the 24th International Symposium on Foundations of Intelligent Systems, ISMIS 2018, held in Limassol, Cyprus, in October 2018. The 32 full, 8 short, and 4 application papers presented in this volume were carefully reviewed and selected from 59 submissions. The papers deal with topics such as bioinformatics and health informatics, graph mining, image analysis, intelligent systems, mining complex patterns, novelty detection and class imbalance, social data analysis, spatio-temporal analysis, and topic modeling and opinion mining. In addition, three special sessions were organized, namely: Special Session on Granular and Soft Clustering for Data Science, Special Session on Intelligent Methodologies for Traffic Data Analysis and Mining, and Special Session on Advanced Methods in Machine Learning for Modeling Complex Data.
Graphs, Morphisms and Statistical Physics
Based on a March 2001 workshop, this collection explores connections between random graphs and percolation, between slow mixing and phase transition, and between graph morphisms and hard-constraint models. Topics of the 14 papers include efficient local search near phase transitions in combinatorial optimization, graph homomorphisms and long range action, recent results on parameterized H-colorings, the satisfiability of random k-Horn formulae, a discrete non-Pfaffian approach to the Ising problem, and chromatic numbers of products of tournaments. No indexes are provided. Annotation : 2004 Book News, Inc., Portland, OR (booknews.com).
Computational Modeling and Problem Solving in the Networked World
This book is a compilation of a selected subset of research articles presented at the Eighth INFORMS Computing Society Conference, held in Chandler, Arizona, from January 8 to 10, 2003. The articles in this book represent the diversity and depth of the interface between ORiMS (operations research and the management sciences) and CS/AI (computer science and artificial intelligence ). This volume starts with two papers that represent the reflective and integrative thinking that is critical to any scientific discipline. These two articles present philosophical perspectives on computation, covering a variety of traditional and newer methods for modeling, solving, and explaining mathematical mode...
Genetic and Evolutionary Computation--GECCO 2003
The set LNCS 2723 and LNCS 2724 constitutes the refereed proceedings of the Genetic and Evolutionaty Computation Conference, GECCO 2003, held in Chicago, IL, USA in July 2003. The 193 revised full papers and 93 poster papers presented were carefully reviewed and selected from a total of 417 submissions. The papers are organized in topical sections on a-life adaptive behavior, agents, and ant colony optimization; artificial immune systems; coevolution; DNA, molecular, and quantum computing; evolvable hardware; evolutionary robotics; evolution strategies and evolutionary programming; evolutionary sheduling routing; genetic algorithms; genetic programming; learning classifier systems; real-world applications; and search based softare engineering.
Algorithms and Models for the Web Graph
This book constitutes the refereed proceedings of the 10th International Workshop on Algorithms and Models for the Web Graph, WAW 2013, held in Cambridge, MA, USA, in December 2013. The 17 papers presented were carefully reviewed and selected for inclusion in this volume. They address topics related to graph-theoretic and algorithmic aspects of related complex networks, including citation networks, social networks, biological networks, molecular networks and other networks arising from the Internet.
Unifying Themes in Complex Systems VII
The International Conference on Complex Systems (ICCS) creates a unique atmosphere for scientists of all fields, engineers, physicians, executives, and a host of other professionals to explore common themes and applications of complex system science. With this new volume, Unifying Themes in Complex Systems continues to build common ground between the wide-ranging domains of complex system science.
