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Author, Editor

Author(s):

Case, John
Kötzing, Timo

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dblp

Not MPG Author(s):

Case, John

Editor(s):

Kalai, Adam Tauman
Mohri, Mehryar

dblp
dblp

Not MPII Editor(s):

Kalai, Adam Tauman
Mohri, Mehryar

BibTeX cite key*:

Koetzing2010NUTechniques

Title, Booktitle

Title*:

Strongly Non-U-Shaped Learning Results by General Techniques

Booktitle*:

COLT 2010 : The 23rd Conference on Learning Theory

Event, URLs

URL of the conference:


URL for downloading the paper:

http://www.colt2010.org/papers/011koetzing.pdf

Event Address*:

Haifa, Israel

Language:

English

Event Date*
(no longer used):


Organization:


Event Start Date:

27 June 2010

Event End Date:

29 June 2010

Publisher

Name*:

Omnipress

URL:


Address*:

Madison, WI

Type:


Vol, No, Year, pp.

Series:


Volume:


Number:


Month:


Pages:

181-193

Year*:

2010

VG Wort Pages:


ISBN/ISSN:

978-0-9822529-2-5

Sequence Number:


DOI:




Note, Abstract, ©


(LaTeX) Abstract:

In learning, a semantic or behavioral
U-shape occurs when a learner first learns, then unlearns, and, finally,
relearns, some target concept (on the way to success).
Within the framework of Inductive Inference,
previous results have shown, for example, that such
U-shapes are unnecessary for
explanatory learning, but are necessary for behaviorally correct and
non-trivial vacillatory learning. Herein we focus more on syntactic
U-shapes.

This paper introduces two general techniques
and applies them especially to syntactic U-shapes in learning:
one technique to show when they are necessary and one to show when they are
unnecessary. The technique for the former is very general and applicable
to a much wider range of learning criteria. It employs so-called
\emph{self-learning classes of languages} which are shown to
\emph{characterize} completely one criterion learning more than another.

We apply these techniques to show that, for set-driven and partially set-driven
learning, any kind of U-shapes are unnecessary. Furthermore,
we show that U-shapes are \emph{not} unnecessary in a strong way for iterative
learning, contrasting an earlier result by Case and Moelius that semantic
U-shapes \emph{are} unnecessary for iterative learning.



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Access Level:

Public

Correlation

MPG Unit:

Max-Planck-Institut für Informatik



MPG Subunit:

Algorithms and Complexity Group

Appearance:

MPII WWW Server, MPII FTP Server, MPG publications list, university publications list, working group publication list, Fachbeirat, VG Wort



BibTeX Entry:

@INPROCEEDINGS{Koetzing2010NUTechniques,
AUTHOR = {Case, John and K{\"o}tzing, Timo},
EDITOR = {Kalai, Adam Tauman and Mohri, Mehryar},
TITLE = {Strongly Non-{U}-Shaped Learning Results by General Techniques},
BOOKTITLE = {COLT 2010 : The 23rd Conference on Learning Theory},
PUBLISHER = {Omnipress},
YEAR = {2010},
PAGES = {181--193},
ADDRESS = {Haifa, Israel},
ISBN = {978-0-9822529-2-5},
}


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Created
12/13/2010 03:55:00 PM
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12/13/2010 04:03:16 PM
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