Handling noise in Boolean matrix factorization

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F17%3A73582745" target="_blank" >RIV/61989592:15310/17:73582745 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.24963/ijcai.2017/198" target="_blank" >http://dx.doi.org/10.24963/ijcai.2017/198</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.24963/ijcai.2017/198" target="_blank" >10.24963/ijcai.2017/198</a>

Result language
angličtina
Original language name
Handling noise in Boolean matrix factorization
Original language description
We critically examine and point out weaknesses of the existing considerations in Boolean matrix factorization (BMF) regarding noise and the algorithms' ability to deal with noise. We argue that the current understanding is underdeveloped and that the current approaches are missing an important aspect. We provide a new, quantitative way to assess the ability of an algorithm to handle noise. Our approach is based on a common-sense definition of robustness requiring that the computed factorizations should not be affected much by varying the noise in data. We present an experimental evaluation of several existing algorithms and compare the results to the observations available in the literature. In addition to providing justification of some properties claimed in the literature without proper justification, our experiments reveal properties which were not reported as well as properties which counter certain claims made in the literature. Importantly, our approach reveals a line separating robust-to-noise from sensitive-to-noise algorithms, which has not been revealed by the previous approaches.
Czech name
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Czech description
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Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project
<a href="/en/project/GA15-17899S" target="_blank" >GA15-17899S: Decompositions of Matrices with Boolean and Ordinal Data: Theory and Algorithms</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
26th International Joint Conference on Artificial Intelligence, IJCAI 2017
ISBN
978-0-9992411-0-3
ISSN
1045-0823
e-ISSN
neuvedeno
Number of pages
7
Pages from-to
1433-1439
Publisher name
International Joint Conferences on Artificial Intelligence
Place of publication
Melbourne
Event location
Melbourne
Event date
Aug 19, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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