Learn IT - Books tags computation

Elements of Quantum Computing: History, Theories and Engineering Applications

Springer, 2014

A quantum computer is a computer based on a computational model which uses quantum mechanics, which is a subfield of physics to study phenomena at the micro level. There has been a growing interest on quantum computing in the 1990's and some quantum computers at the experimental level were recently implemented. Quantum computers enable...

The Theory of Computation

Addison Wesley, 1997

This is the best text on complexity theory I have seen, and could easily become the standard text on the subject...This is the first modern text on the theory of computing. ---William Ward Jr, Ph.D, University of South Alabama

Taking a practical approach, this modern introduction to the theory of computation focuses on the study of...

Discrete Mathematics for Computing (Grassroots)

Palgrave Macmillan, 2002

This book is an introductory text on a number of topics in discrete mathematics, intended primarily for students undertaking a first degree in computing. The first edition of the book grew out of a set of lecture notes of mine which were used in a first-year subject in discrete mathematics at Monash University. The subject was taken by students...

Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)

MIT Press, 2005

Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning community over the past decade, and this book provides a long-needed systematic and unified treatment of theoretical and practical aspects of GPs in machine learning. The...

Computational Mind: A Complex Dynamics Perspective (Studies in Computational Intelligence)

Springer, 2007

Computational Mind: A Complex Dynamics Perspective is a graduate–level monographic textbook in the field of Computational Intelligence. It presents a modern dynamical theory of the computational mind, combining cognitive psychology, artificial and computational intelligence, and chaos theory with quantum consciousness and computation. The...

Phase Transitions in Machine Learning

Cambridge University Press, 2011

From its inception in the 1930s, the rich and vigorous field of computer science has been concerned with the resources, both in time and in memory, needed to carry out a computation. A number of fundamental theorems were discovered that resorted to a worst-case analysis. The central question was whether a given algorithm could be...

Algorithms and Computation: 20th International Symposium, ISAAC 2009, Honolulu, Hawaii

Springer, 2010

The papers in this volume were presented at the 20th Annual International Symposium on Algorithms and Computation, held December 16–18, 2009, in Hawaii, USA. In response to the Call-for-Papers, 279 papers were submitted. Each paper received at least three reviews by either Program Committee members or experts selected by Program...

New Challenges in Applied Intelligence Technologies (Studies in Computational Intelligence)

Springer, 2008

The field of intelligence technologies covers a variety of computational approaches that are often suggested and inspired by biological systems, exhibiting functional richness and flexibility of natural behavior. This class of technologies consists of such important approaches as data mining algorithms, neural networks, genetic algorithms, fuzzy...

Unconventional Computation: 7th International Conference, UC 2008, Vienna, Austria, August 25-28, 2008, Proceedings

Springer, 2008

This book constitutes the refereed proceedings of the 7th International Conference on Unconventional Computation, UC 2008, held in Vienna, Austria, in August 2008.

The 16 revised full papers presented together with 4 invited papers were carefully reviewed and selected for inclusion in the book. The papers are devoted to all aspects of...

Modeling and Computation in Engineering II

CRC Press, 2013

Modeling and Computation in Engineering II (CMCE 2013, Hong Kong, 22-23 June 2013) includes 50 contributions on modeling and simulation technology, which were presented at the 2nd SREE Conference on Modeling and Computation in Engineering (CMCE 2013) and the 3rd SREE Workshop on Applied Mechanics and Civil Engineering...

Adaptive Learning of Polynomial Networks: Genetic Programming, Backpropagation and Bayesian Methods

Springer, 2006

This book delivers theoretical and practical knowledge for developing algorithms that infer linear and non-linear multivariate models, providing a methodology for inductive learning of polynomial neural network models (PNN) from data. The text emphasizes an organized model identification process by which to discover models that generalize and...

Deep Learning with Python: A Hands-on Introduction

Apress, 2017

Discover the practical aspects of implementing deep-learning solutions using the rich Python ecosystem. This book bridges the gap between the academic state-of-the-art and the industry state-of-the-practice by introducing you to deep learning frameworks such as Keras, Theano, and Caffe. The practicalities of these frameworks is often...

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