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The Bayesian Choice: From Decision-Theoretic Foundations to Computational Implementation (Springer Texts in Statistics)
The Bayesian Choice: From Decision-Theoretic Foundations to Computational Implementation (Springer Texts in Statistics)

The main purpose of statistical theory is to derive from observations of a random phenomenon an inference about the probability distribution underlying this phenomenon. That is, it provides either an analysis (description) of a past phenomenon, or some predictions about a future phenomenon of a similar nature. In this book, we insist...

Parallel and Distributed Logic Programming: Towards the Design of a Framework for the Next Generation Database Machines
Parallel and Distributed Logic Programming: Towards the Design of a Framework for the Next Generation Database Machines
Foundation of logic historically dates back to the times of Aristotle, who pioneered the concept of truth/falsehood paradigm in reasoning. Mathematical logic of propositions and predicates, which are based on the classical models of Aristotle, underwent a dramatic evolution during the last 50 years for its increasing applications in automated...
Numerical Issues in Statistical Computing for the Social Scientist (Wiley Series in Probability and Statistics)
Numerical Issues in Statistical Computing for the Social Scientist (Wiley Series in Probability and Statistics)
At last—a social scientist's guide through the pitfalls of modern statistical computing
Addressing the current deficiency in the literature on statistical methods as they apply to the social and behavioral sciences, Numerical Issues in Statistical Computing for the Social Scientist seeks to provide readers with a unique practical
...
Java The Complete Reference, 8th Edition
Java The Complete Reference, 8th Edition

The Definitive Java Programming Guide

In Java: The Complete Reference, Eighth Edition, bestselling programming author Herb Schildt shows you everything you need to develop, compile, debug, and run Java programs. Updated for Java Platform, Standard Edition 7 (Java SE 7), this comprehensive volume covers the entire Java...

Canon EOS 70D
Canon EOS 70D

The logic for determining the significance of model numbers for the various Canon DSLR models can appear nonexistent. By inference, we've concluded that the EOS ID series—with its various alphabetic suffixes and Mark qualifiers—is the top-of-the-line professional DSLR body. Other single-digit D- series DSLR bodies are...

Conceptual Structures: Knowledge Architectures for Smart Applications: 15th International Conference on Conceptual Structures, ICCS 2007, Sheffield
Conceptual Structures: Knowledge Architectures for Smart Applications: 15th International Conference on Conceptual Structures, ICCS 2007, Sheffield
Conceptual Graphs (CG, www.conceptualgraphs.org) provide a powerful knowledge representation and inference environment, whilst exhibiting the familiar objectoriented and database features of contemporary enterprise and web applications. CG capture nuances in natural language whilst being able to be implemented in computer...
Learning Theory: 17th Annual Conference on Learning Theory, COLT 2004, Banff, Canada, July 1-4, 2004, Proceedings
Learning Theory: 17th Annual Conference on Learning Theory, COLT 2004, Banff, Canada, July 1-4, 2004, Proceedings
This book constitutes the refereed proceedings of the 17th Annual Conference on Learning Theory, COLT 2004, held in Banff, Canada in July 2004.

The 46 revised full papers presented were carefully reviewed and selected from a total of 113 submissions. The papers are organized in topical sections on economics and game theory, online learning,...

Graphical Models for Machine Learning and Digital Communication (Adaptive Computation and Machine Learning)
Graphical Models for Machine Learning and Digital Communication (Adaptive Computation and Machine Learning)

A variety of problems m machine learning and digital communication deal with complex but structured natural or artificial systems. Natural patterns mat we wish to automatically classify' are a consequence of a hierarchical causal physical process. Learning about the world m which we live requires mat we extract useful sensor)'...

Mastering Probabilistic Graphical Models using Python
Mastering Probabilistic Graphical Models using Python

Master probabilistic graphical models by learning through real-world problems and illustrative code examples in Python

About This Book

  • Gain in-depth knowledge of Probabilistic Graphical Models
  • Model time-series problems using Dynamic Bayesian Networks
  • A practical guide to...
Sets, Logic and Maths for Computing (Undergraduate Topics in Computer Science)
Sets, Logic and Maths for Computing (Undergraduate Topics in Computer Science)
This book equips the student with essential intellectual tools that are needed from the very beginning of university studies in computing. These consist of abilities and skills - to pass from a concrete problem to an abstract representation, reason with the abstract structure coherently and usefully, and return with booty to the specific situation....
Computer Vision: Models, Learning, and Inference
Computer Vision: Models, Learning, and Inference

There are already many computer vision textbooks, and it is reasonable to question the need for another. Let me explain why I chose to write this volume.

Computer vision is an engineering discipline; we are primarily motivated by the real-world concern of...

Mathematics of Fuzzy Sets and Fuzzy Logic (Studies in Fuzziness and Soft Computing)
Mathematics of Fuzzy Sets and Fuzzy Logic (Studies in Fuzziness and Soft Computing)

This book presents a mathematically-based introduction into the fascinating topic of Fuzzy Sets and Fuzzy Logic and might be used as textbook at both undergraduate and graduate levels and also as reference guide for mathematician, scientists or engineers who would like to get an insight into Fuzzy Logic.

Fuzzy Sets have been...

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