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Metric-Based Approaches for Semi-Supervised Regression and Classification

Schuurmans Dale, Southey Finnegan, Wilkinson Dana, and Guo Yuhong

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/9780262033589.003.0023
Subject:
Computer Science, Machine Learning

This chapter discusses the explicit relationship that must be asserted between labeled and unlabeled data, which is a requirement of semi-supervised learning methods. Semi-supervised model selection ... More


The Geometric Basis of Semi-Supervised Learning

Sindhwani Vikas, Belkin Misha, and Niyogi Partha

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/9780262033589.003.0012
Subject:
Computer Science, Machine Learning

This chapter presents an algorithmic framework for semi-supervised inference based on geometric properties of probability distributions. This approach brings together Laplacian-based spectral ... More


Renormalisation I: Perturbation theory

Michael Kachelriess

in Quantum Fields: From the Hubble to the Planck Scale

Published in print:
2017
Published Online:
February 2018
ISBN:
9780198802877
eISBN:
9780191841330
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/oso/9780198802877.003.0011
Subject:
Physics, Particle Physics / Astrophysics / Cosmology, Theoretical, Computational, and Statistical Physics

After giving an overview about regularisation and renormalisation methods, this chapter shows the calculation of the anomalous magnetic moment of the electron in QED. Using a power counting argument, ... More


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