As the complexity of software increases, researchers and practicioners continue to seek better techniques for engineering the construction of evolution of software. Partial evaluation is an attractive technology for modern software construction since it provides automatic tools for software specialization and is based on rigorous semantic foundations. This book is based on a school held at DIKU Copenhagen, Denmark in summer 1998 during which leading researchers summarized the state of the art in partial evaluation. The lectures presented survey the foundations of partial evaluation in a clear and rigorous manner and practically introduce several existing partial evaluators with numerous examples. The second part of the book is devoted to more sophisticated theoretical aspects, advances systems and applications, and highlights open problems and challenges. The book is ideally suited for advanced courses and for self study.
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Describing non-parametric and parametric theoretic classification and the training of discriminant functions, this second edition includes new and expanded sections on neural networks, Fisher’s discriminant, wavelet transform, and the method of principal components. It contains discussions on dimensionality reduction and feature selection, novel computer system architectures, proven algorithms for solutions to common roadblocks in data processing, computing models including the Hamming net, the Kohonen self-organizing map, and the Hopfield net, detailed appendices with data sets illustrating key concepts in the text, and more.
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