Learn IT - MIT Press

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PVM: Parallel Virtual Machine: A Users' Guide and Tutorial for Network Parallel Computing

MIT Press, 1994

Written by the team that developed the software, this tutorial is the definitive resource for scientists, engineers, and other computer users who want to use PVM to increase the flexibility and power of their high-performance computing resources. PVM introduces distributed computing, discusses where and how to get the PVM software,...

Privacy on the Line: The Politics of Wiretapping and Encryption

MIT Press, 1998

In the spring of 1993, the White House announced an unprecedented plan for both promoting and
controlling the use of secret codes to keep communications private. The plan, formally called key
escrow but popularly known as "Clipper" after its star component, the Clipper chip, was to adopt a
new federal standard for...

Automatic Algorithm Recognition and Replacement: A New Approach to Program Optimization

MIT Press, 2000

Optimizing compilers have a fundamental problem. No matter how powerful their optimizations
are, they are no substitute for good application algorithms. Consider the case of
sorting. For sufficiently large data sets, a merge sort algorithm compiled with a less powerful
optimizer will always out-perform a selection sort algorithm...

Principles of Data Mining (Adaptive Computation and Machine Learning)

MIT Press, 2001

The growing interest in data mining is motivated by a common problem across disciplines: how does one store, access, model, and ultimately describe and understand very large data sets? Historically, different aspects of data mining have been addressed independently by different disciplines. This is the first truly...

Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence

MIT Press, 1999

The study of multiagent systems began in the field of distributed artificial intelligence (DAI) about 20 years
ago. Today these systems are not simply a research topic, but are also beginning to become an important subject of
academic teaching and industrial and commercial application. While there are several high-quality collections of...

How to Design Programs: An Introduction to Programming and Computing

MIT Press, 2001

This introduction to programming places computer science in the core of a liberal arts education. Unlike other introductory books, it focuses on the program design process. This approach fosters a variety of skills--critical reading, analytical thinking, creative synthesis, and attention to detail - that are important for everyone, not just future...

An Introduction to Genetic Algorithms (Complex Adaptive Systems)

MIT Press, 1998

Science arises from the very human desire to understand and control the world. Over the course of history, we
humans have gradually built up a grand edifice of knowledge that enables us to predict, to varying extents, the
weather, the motions of the planets, solar and lunar eclipses, the courses of diseases, the rise and fall...

C# Precisely

MIT Press, 2004

This book describes the programming language C# (pronounced “c sharp”), version 2.0. It is a quick reference for the reader who has already learnt or is learning C# from a standard textbook and who wants to know the language in more detail. It should be particularly useful for readers who know the Java programming language and who want...

Computability and Complexity: From a Programming Perspective (Foundations of Computing)

MIT Press, 1997

Computability and complexity theory should be of central concern to practitioners as well as theorists. Unfortunately, however, the field is known for its impenetrability. Neil Jones's goal as an educator and author is to build a bridge between computability and complexity theory and other areas of computer science, especially programming. In a...

Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering

MIT Press, 1996

Here we have a comprehensive, problem-oriented, engineering perspective on the uses of neural nets, fuzzy systems, and hybrids that emphasizes practical solutions to everyday artificial intelligence (AI) problems over abstract theoretical noodling. Intended for upper-division students and postgraduates who need a...

Advanced Topics in Types and Programming Languages

MIT Press, 2004

Work in type systems for programming languages now touches many parts
of computer science, from language design and implementation to software
engineering, network security, databases, and analysis of concurrent and distributed
systems. The aim of this book, together with its predecessor, Types
and Programming Languages (Pierce...

Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond

MIT Press, 2001

In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of SVMs—-kernels--for a number of learning tasks. Kernel machines provide a modular framework...

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