Rodrigo Fernandes de Mello

Laurence T. Yang

Ronald Perrott

Barbara Chapman

Jaspal Subhlok

This book constitutes the refereed proceedings of the Third International Conference on High Performance Computing and Communications, HPCC 2007, held in Houston, USA, September 26-28, 2007. The 75 revised full papers presented were carefully reviewed and selected from 272 submissions. The papers address all current issues of parallel and distributed systems and high performance computing and communication as there are: networking protocols, routing, and algorithms, languages and compilers for HPC, parallel and distributed architectures and algorithms, embedded systems, wireless, mobile and pervasive computing, Web services and internet computing, peer-to-peer computing, grid and cluster computing, reliability, fault-tolerance, and security, performance evaluation and measurement, tools and environments for software development, distributed systems and applications, database applications and data mining, biological/molecular computing, collaborative and cooperative environments, and programming interfaces for parallel systems.

Third International Conference, HPCC 2007, Houston, USA, September 26-28, 2007, Proceedings

High Performance Computing and Communications

This book constitutes the refereed proceedings of the Third International Conference on High Performance Computing and Communications, HPCC 2007. The 75 revised full papers address all current issues of parallel and distributed systems and high performance computing and communication, including networking protocols, embedded systems, wireless, mobile and pervasive computing, Web services and internet computing, and programming interfaces for parallel systems.

Moacir Antonelli Ponti

This book presents the Statistical Learning Theory in a detailed and easy to understand way, by using practical examples, algorithms and source codes. It can be used as a textbook in graduation or undergraduation courses, for self-learners, or as reference with respect to the main theoretical concepts of Machine Learning. Fundamental concepts of Linear Algebra and Optimization applied to Machine Learning are provided, as well as source codes in R, making the book as self-contained as possible. It starts with an introduction to Machine Learning concepts and algorithms such as the Perceptron, Multilayer Perceptron and the Distance-Weighted Nearest Neighbors with examples, in order to provide the necessary foundation so the reader is able to understand the Bias-Variance Dilemma, which is the central point of the Statistical Learning Theory. Afterwards, we introduce all assumptions and formalize the Statistical Learning Theory, allowing the practical study of different classification algorithms. Then, we proceed with concentration inequalities until arriving to the Generalization and the Large-Margin bounds, providing the main motivations for the Support Vector Machines. From that, we introduce all necessary optimization concepts related to the implementation of Support Vector Machines. To provide a next stage of development, the book finishes with a discussion on SVM kernels as a way and motivation to study data spaces and improve classification results.

A Practical Approach on the Statistical Learning Theory

Machine Learning

Weijia Jia

Ruppa K. Thulasiram

Minyi Guo

Ivan Stojmenovic

This book constitutes the refereed proceedings of the 5th International Symposium on Parallel and Distributed Processing and Applications, ISPA 2007, held in Niagara Falls, Canada, in August 2007. The 83 revised full papers presented together with 3 keynote speeches were carefully reviewed and selected from 244 submissions. The papers are organized in topical sections on algorithms and applications, architectures and systems, datamining and databases, fault tolerance and security, middleware and cooperative computing, networks, as well as software and languages.

5th International Symposium, ISPA 2007, Niagara Falls, Canada, August 29-31, 2007, Proceedings

Parallel and Distributed Processing and Applications

This book constitutes the refereed proceedings of the 5th International Symposium on Parallel and Distributed Processing and Applications, ISPA 2007, held in Niagara Falls, Canada, in August 2007. The 83 revised full papers presented together with three keynote are cover algorithms and applications, architectures and systems, datamining and databases, fault tolerance and security, middleware and cooperative computing, networks, as well as software and languages.

Rodrigo Fernandes de Mello

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