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Wang SZhou AZhang GFang F(2023)Learning Regularity for Evolutionary Multiobjective Search: A Generative Model-Based ApproachIEEE Computational Intelligence Magazine10.1109/MCI.2023.330408018:4(29-42)Online publication date: 1-Nov-2023
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Gjoreski HRoggen DLee STakayama LTruong KHealey JPloetz T(2017)Unsupervised online activity discovery using temporal behaviour assumptionProceedings of the 2017 ACM International Symposium on Wearable Computers10.1145/3123021.3123044(42-49)Online publication date: 11-Sep-2017
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Kompella VLuciw MStollenga MSchmidhuber J(2016)Optimal curiosity-driven modular incremental slow feature analysisNeural Computation10.1162/NECO_a_0085528:8(1599-1662)Online publication date: 1-Aug-2016
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An on-line agglomerative clustering method for nonstationary data
1. Computing methodologies
2. Theory of computation
  1. Design and analysis of algorithms

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Published In

Neural Computation Volume 11, Issue 2

Feb. 15, 1999

255 pages

ISSN:0899-7667

Editor:
Terrence Sejnowski
Univ. of California at San Diego

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MIT Press

Cambridge, MA, United States

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Published: 01 February 1999

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https://dl.acm.org/doi/10.1109/MCI.2023.3304080
Gjoreski HRoggen DLee STakayama LTruong KHealey JPloetz T(2017)Unsupervised online activity discovery using temporal behaviour assumptionProceedings of the 2017 ACM International Symposium on Wearable Computers10.1145/3123021.3123044(42-49)Online publication date: 11-Sep-2017
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Design and evaluation of clustering criterion for optimal hierarchical agglomerative clustering

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