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Algorithms, Agents, and Ontologies

Paul Kockelman

in The Art of Interpretation in the Age of Computation

Published in print:
2017
Published Online:
July 2017
ISBN:
9780190636531
eISBN:
9780190636562
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780190636531.003.0007
Subject:
Linguistics, Sociolinguistics / Anthropological Linguistics

This chapter details the inner workings of spam filters, algorithmic devices that separate desirable messages from undesirable messages. It argues that such filters are a particularly important kind ... More


Dataset Shift in Machine Learning

Joaquin Quiñonero-Candela, Masashi Sugiyama, Anton Schwaighofer, and Neil D. Lawrence (eds)

Published in print:
2008
Published Online:
August 2013
ISBN:
9780262170055
eISBN:
9780262255103
Item type:
book
Publisher:
The MIT Press
DOI:
10.7551/mitpress/9780262170055.001.0001
Subject:
Computer Science, Machine Learning

Dataset shift is a common problem in predictive modeling that occurs when the joint distribution of inputs and outputs differs between training and test stages. Covariate shift, a particular case of ... More


An Adversarial View of Covariate Shift and a Minimax Approach

Globerson Amir, Hui Teo Choon, Smola Alex, and Roweis Sam

in Dataset Shift in Machine Learning

Published in print:
2008
Published Online:
August 2013
ISBN:
9780262170055
eISBN:
9780262255103
Item type:
chapter
Publisher:
The MIT Press
DOI:
10.7551/mitpress/9780262170055.003.0010
Subject:
Computer Science, Machine Learning

This chapter considers an adversarial model where the learning algorithm attempts to construct a predictor that is robust to deletion of features at test time. The problem is formulated as finding ... More


Statistical thinking in a data science course

Andrew Gelman and Deborah Nolan

in Teaching Statistics: A Bag of Tricks

Published in print:
2017
Published Online:
September 2017
ISBN:
9780198785699
eISBN:
9780191827518
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/oso/9780198785699.003.0021
Subject:
Mathematics, Educational Mathematics

In this chapter, we describe the philosophy, goals, syllabus, and activities for a course that we have developed in data science course. In this course we integrate topics from computing, statistics, ... More


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