Jump to ContentJump to Main Navigation

You are looking at 1-4 of 4 items

  • Keywords: real-world problems x
Clear All Modify Search

View:

Introduction

Jörg Liesen and Zdenek Strakos

in Krylov Subspace Methods: Principles and Analysis

Published in print:
2012
Published Online:
January 2013
ISBN:
9780199655410
eISBN:
9780191744174
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199655410.003.0001
Subject:
Mathematics, Applied Mathematics, Algebra

The Introduction consists of three sections that establish the general setting and give background information that is useful to know before starting to read the other chapters. In particular, it ... More


Being Productively Wrong

Luis Perez-Breva and Nick Fuhrer

in Innovating: A Doer's Manifesto for Starting from a Hunch, Prototyping Problems, Scaling Up, and Learning to Be Productively Wrong

Published in print:
2017
Published Online:
September 2017
ISBN:
9780262035354
eISBN:
9780262336680
Item type:
chapter
Publisher:
The MIT Press
DOI:
10.7551/mitpress/9780262035354.003.0001
Subject:
Business and Management, Innovation

At its genesis, no thing about an eventual innovation is new. It is only in hindsight that the stories of innovations become streamlined, linear accounts of success. Actual innovating, like learning, ... More


Capturing Attention in the Laboratory and the Real World

Walter R. Boot, Arthur F. Kramer, and Ensar Becic

in Attention: From Theory to Practice

Published in print:
2006
Published Online:
March 2012
ISBN:
9780195305722
eISBN:
9780199847723
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780195305722.003.0003
Subject:
Psychology, Cognitive Psychology

Researchers have long been interested in the forces that control the movement of visual attention. As far back as the writings of William James (1842–1910), psychologists have made the distinction ... More


Analysis of Benchmarks

Chapelle Olivier, Schölkopf Bernhard, and Zien Alexander

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/9780262033589.003.0021
Subject:
Computer Science, Machine Learning

This chapter assesses the strengths and weaknesses of different semi-supervised learning (SSL) algorithms through inviting the authors of each chapter in this book to apply their algorithms to eight ... More


View: