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Morgan Kaufmann

    • Practical Neural Network Recipies in C++

      • 1st Edition
      • Masters
      • English
      This text serves as a cookbook for neural network solutions to practical problems using C++. It will enable those with moderate programming experience to select a neural network model appropriate to solving a particular problem, and to produce a working program implementing that network. The book provides guidance along the entire problem-solving path, including designing the training set, preprocessing variables, training and validating the network, and evaluating its performance. Though the book is not intended as a general course in neural networks, no background in neural works is assumed and all models are presented from the ground up.The principle focus of the book is the three layer feedforward network, for more than a decade as the workhorse of professional arsenals. Other network models with strong performance records are also included.Bound in the book is an IBM diskette that includes the source code for all programs in the book. Much of this code can be easily adapted to C compilers. In addition, the operation of all programs is thoroughly discussed both in the text and in the comments within the code to facilitate translation to other languages.

    • Foundations of Genetic Algorithms 1993 (FOGA 2)

      • 1st Edition
      • Volume 2
      • FOGA
      • English
      Foundations of Genetic Algorithms, Volume 2 provides insight of theoretical work in genetic algorithms. This book provides a general understanding of a canonical genetic algorithm. Organized into six parts encompassing 19 chapters, this volume begins with an overview of genetic algorithms in the broader adaptive systems context. This text then reviews some results in mathematical genetics that use probability distributions to characterize the effects of recombination on multiple loci in the absence of selection. Other chapters examine the static building block hypothesis (SBBH), which is the underlying assumption used to define deception. This book discusses as well the effect of noise on the quality of convergence of genetic algorithms. The final chapter deals with the primary goal in machine learning and artificial intelligence, which is to dynamically and automatically decompose problems into simpler problems to facilitate their solution. This book is a valuable resource for theorists and genetic algorithm researchers.

    • Readings in Groupware and Computer-Supported Cooperative Work

      Assisting Human-Human Collaboration
      • 1st Edition
      • Ronald M. Baecker
      • English
      This comprehensive introduction to the field represents the best of the published literature on groupware and computer-supported cooperative work (CSCW). The papers were chosen for their breadth of coverage of the field, their clarity of expression and presentation, their excellence in terms of technical innovation or behavioral insight, their historical significance, and their utility as sources for further reading. Taken as a whole, the papers and their introductions are a complete sourcebook to the field. This book will be useful for computer professionals involved in the development or purchase of groupware technology as well as for researchers and managers. It should also serve as a valuable text for university courses on CSCW, groupware, and human-computer interaction.

    • Physically-Based Modeling for Computer Graphics

      A Structured Approach
      • 1st Edition
      • Ronen Barzel + 1 more
      • English
      Physically-Based Modeling for Computer Graphics: A Structured Approach addresses the challenge of designing and managing the complexity of physically-based models. This book will be of interest to researchers, computer graphics practitioners, mathematicians, engineers, animators, software developers and those interested in computer implementation and simulation of mathematical models.

    • C4.5

      Programs for Machine Learning
      • 1st Edition
      • J. Ross Quinlan
      • English
      Classifier systems play a major role in machine learning and knowledge-based systems, and Ross Quinlan's work on ID3 and C4.5 is widely acknowledged to have made some of the most significant contributions to their development. This book is a complete guide to the C4.5 system as implemented in C for the UNIX environment. It contains a comprehensive guide to the system's use , the source code (about 8,800 lines), and implementation notes. C4.5 starts with large sets of cases belonging to known classes. The cases, described by any mixture of nominal and numeric properties, are scrutinized for patterns that allow the classes to be reliably discriminated. These patterns are then expressed as models, in the form of decision trees or sets of if-then rules, that can be used to classify new cases, with emphasis on making the models understandable as well as accurate. The system has been applied successfully to tasks involving tens of thousands of cases described by hundreds of properties. The book starts from simple core learning methods and shows how they can be elaborated and extended to deal with typical problems such as missing data and over hitting. Advantages and disadvantages of the C4.5 approach are discussed and illustrated with several case studies. This book should be of interest to developers of classification-based intelligent systems and to students in machine learning and expert systems courses.

    • Understanding the New SQL

      A Complete Guide
      • 1st Edition
      • Jim Melton + 1 more
      • English
      An effective introduction to SQL, and a comprehensive reference for years to come. As the editor of the 1992 standard, Jim Melton is an authority on the language and its new features. Using a highly readable, conversational style, he and Alan Simon clearly present the power of SQL. They describe practical methods of using SQL to solve problems, advanced SQL query expressions, dynamic SQL, transaction models, and database design.

    • Transaction Processing

      Concepts and Techniques
      • 1st Edition
      • Jim Gray + 1 more
      • English
      The key to client/server computing.Transactio... processing techniques are deeply ingrained in the fields ofdatabases and operating systems and are used to monitor, control and updateinformation in modern computer systems. This book will show you how large,distributed, heterogeneous computer systems can be made to work reliably.Using transactions as a unifying conceptual framework, the authors show howto build high-performance distributed systems and high-availabilityapp... with finite budgets and risk.The authors provide detailed explanations of why various problems occur aswell as practical, usable techniques for their solution. Throughout the book,examples and techniques are drawn from the most successful commercial andresearch systems. Extensive use of compilable C code fragments demonstratesthe many transaction processing algorithms presented in the book. The bookwill be valuable to anyone interested in implementing distributed systemsor client/server architectures.

    • Pattern Recognition and Machine Learning

      • 1st Edition
      • Y. Anzai
      • English
      This is the first text to provide a unified and self-contained introduction to visual pattern recognition and machine learning. It is useful as a general introduction to artifical intelligence and knowledge engineering, and no previous knowledge of pattern recognition or machine learning is necessary. Basic for various pattern recognition and machine learning methods. Translated from Japanese, the book also features chapter exercises, keywords, and summaries.

    • Paradigms of Artificial Intelligence Programming

      Case Studies in Common Lisp
      • 1st Edition
      • Peter Norvig
      • English
      Paradigms of AI Programming is the first text to teach advanced Common Lisp techniques in the context of building major AI systems. By reconstructing authentic, complex AI programs using state-of-the-art Common Lisp, the book teaches students and professionals how to build and debug robust practical programs, while demonstrating superior programming style and important AI concepts. The author strongly emphasizes the practical performance issues involved in writing real working programs of significant size. Chapters on troubleshooting and efficiency are included, along with a discussion of the fundamentals of object-oriented programming and a description of the main CLOS functions. This volume is an excellent text for a course on AI programming, a useful supplement for general AI courses and an indispensable reference for the professional programmer.

    • Machine Learning

      A Theoretical Approach
      • 1st Edition
      • Balas K. Natarajan
      • English
      This is the first comprehensive introduction to computational learning theory. The author's uniform presentation of fundamental results and their applications offers AI researchers a theoretical perspective on the problems they study. The book presents tools for the analysis of probabilistic models of learning, tools that crisply classify what is and is not efficiently learnable. After a general introduction to Valiant's PAC paradigm and the important notion of the Vapnik-Chervonenkis dimension, the author explores specific topics such as finite automata and neural networks. The presentation is intended for a broad audience--the author's ability to motivate and pace discussions for beginners has been praised by reviewers. Each chapter contains numerous examples and exercises, as well as a useful summary of important results. An excellent introduction to the area, suitable either for a first course, or as a component in general machine learning and advanced AI courses. Also an important reference for AI researchers.

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