About: Learning Entropy: Multiscale Measure for Incremental Learning     Goto   Sponge   NotDistinct   Permalink

An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

AttributesValues
rdf:type
rdfs:seeAlso
Description
  • First, this paper recalls a recently introduced method of adaptive monitoring of dynamical systems and presents the most recent extension with a multiscale-enhanced approach. Then, it is shown that this concept of real-time data monitoring establishes a novel non-Shannon and non-probabilistic concept of novelty quantification, i.e., Entropy of Learning, or in short the Learning Entropy. This novel cognitive measure can be used for evaluation of each newly measured sample of data, or even of whole intervals. The Learning Entropy is quantified in respect to the inconsistency of data to the temporary governing law of system behavior that is incrementally learned by adaptive models such as linear or polynomial adaptive filters or neural networks. The paper presents this novel concept on the example of gradient descent learning technique with normalized learning rate.
  • First, this paper recalls a recently introduced method of adaptive monitoring of dynamical systems and presents the most recent extension with a multiscale-enhanced approach. Then, it is shown that this concept of real-time data monitoring establishes a novel non-Shannon and non-probabilistic concept of novelty quantification, i.e., Entropy of Learning, or in short the Learning Entropy. This novel cognitive measure can be used for evaluation of each newly measured sample of data, or even of whole intervals. The Learning Entropy is quantified in respect to the inconsistency of data to the temporary governing law of system behavior that is incrementally learned by adaptive models such as linear or polynomial adaptive filters or neural networks. The paper presents this novel concept on the example of gradient descent learning technique with normalized learning rate. (en)
Title
  • Learning Entropy: Multiscale Measure for Incremental Learning
  • Learning Entropy: Multiscale Measure for Incremental Learning (en)
skos:prefLabel
  • Learning Entropy: Multiscale Measure for Incremental Learning
  • Learning Entropy: Multiscale Measure for Incremental Learning (en)
skos:notation
  • RIV/68407700:21220/13:00212013!RIV14-MSM-21220___
http://linked.open...avai/predkladatel
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(TA03020312), S
http://linked.open...iv/cisloPeriodika
  • 10
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 84511
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21220/13:00212013
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • incremental learning; adaptation plot; multiscale; learning entropy; individual sample learning entropy; approximate learning entropy; order of learning entropy; learning entropy of a model; non-Shannon entropy; novelty detection; chaos; time series; HR (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • CH - Švýcarská konfederace
http://linked.open...ontrolniKodProRIV
  • [ADDC56ADD9F9]
http://linked.open...i/riv/nazevZdroje
  • Entropy
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...v/svazekPeriodika
  • 15
http://linked.open...iv/tvurceVysledku
  • Bukovský, Ivo
http://linked.open...ain/vavai/riv/wos
  • 000328486900010
issn
  • 1099-4300
number of pages
http://bibframe.org/vocab/doi
  • 10.3390/e15104159
http://localhost/t...ganizacniJednotka
  • 21220
Faceted Search & Find service v1.16.118 as of Jun 21 2024


Alternative Linked Data Documents: ODE     Content Formats:   [cxml] [csv]     RDF   [text] [turtle] [ld+json] [rdf+json] [rdf+xml]     ODATA   [atom+xml] [odata+json]     Microdata   [microdata+json] [html]    About   
This material is Open Knowledge   W3C Semantic Web Technology [RDF Data] Valid XHTML + RDFa
OpenLink Virtuoso version 07.20.3240 as of Jun 21 2024, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (126 GB total memory, 78 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software