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PRELIMINARIES AND AGREEMENTS

Rolf Niedermeier

in Invitation to Fixed-Parameter Algorithms

Published in print:
2006
Published Online:
September 2007
ISBN:
9780198566076
eISBN:
9780191713910
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780198566076.003.0002
Subject:
Mathematics, Combinatorics / Graph Theory / Discrete Mathematics

This chapter introduces the basic mathematical formalism and discusses concepts used throughout the book. Among other things, it looks at decision problems vs optimization problems, Random Access ... More


Optimization Problems

Hidetoshi Nishimori

in Statistical Physics of Spin Glasses and Information Processing: An Introduction

Published in print:
2001
Published Online:
January 2010
ISBN:
9780198509417
eISBN:
9780191709081
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780198509417.003.0009
Subject:
Physics, Theoretical, Computational, and Statistical Physics

A decision-making problem is often formulated as the minimization or maximization of a multivariable function, an optimization problem. This chapter shows that the methods of statistical mechanics ... More


Multipliers and the LeChatelier Principle

Paul Milgrom

in Samuelsonian Economics and the Twenty-First Century

Published in print:
2006
Published Online:
January 2009
ISBN:
9780199298839
eISBN:
9780191711480
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199298839.003.0020
Subject:
Economics and Finance, History of Economic Thought

This chapter examines Samuelson's Le Chatelier principle of how the market responds to a change in parameters of demand and supply curves. It uses examples in demand theory, economic policy, and ... More


Transductive Support Vector Machines

Joachims Thorsten

in Semi-Supervised Learning

Published in print:
2006
Published Online:
August 2013
ISBN:
9780262033589
eISBN:
9780262255899
Item type:
chapter
Publisher:
The MIT Press
DOI:
10.7551/mitpress/9780262033589.003.0006
Subject:
Computer Science, Machine Learning

This chapter discusses the transductive learning setting proposed by Vapnik where predictions are made only at a fixed number of known test points. Transductive support vector machines (TSVMs) ... More


Semi-Supervised Learning Using Semi-Definite Programming

De Bie Tijl and Cristianini Nello

in Semi-Supervised Learning

Published in print:
2006
Published Online:
August 2013
ISBN:
9780262033589
eISBN:
9780262255899
Item type:
chapter
Publisher:
The MIT Press
DOI:
10.7551/mitpress/9780262033589.003.0007
Subject:
Computer Science, Machine Learning

This chapter discusses an alternative approach that is based on a convex relaxation of the optimization problem associated with support vector machine transduction. The result is a semi-definite ... More


Prediction of Protein Function from Networks

Shin Hyunjung and Tsuda Koji

in Semi-Supervised Learning

Published in print:
2006
Published Online:
August 2013
ISBN:
9780262033589
eISBN:
9780262255899
Item type:
chapter
Publisher:
The MIT Press
DOI:
10.7551/mitpress/9780262033589.003.0020
Subject:
Computer Science, Machine Learning

This chapter describes an algorithm to assign weights to multiple graphs within graph-based semi-supervised learning. Both predicting class labels and searching for weights for combining multiple ... More


Optimal Control Imaging of Extended Inclusions

Habib Ammari, Elie Bretin, Josselin Garnier, Hyeonbae Kang, Hyundae Lee, and Abdul Wahab

in Mathematical Methods in Elasticity Imaging

Published in print:
2015
Published Online:
October 2017
ISBN:
9780691165318
eISBN:
9781400866625
Item type:
chapter
Publisher:
Princeton University Press
DOI:
10.23943/princeton/9780691165318.003.0010
Subject:
Mathematics, Applied Mathematics

This chapter describes the use of time-reversal imaging techniques for optimal control of extended inclusions. It first considers the problem of reconstructing shape deformations of an extended ... More


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