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  • Search: subject:"Representation Learning"
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Year of publication
Subject
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Theorie 4 Theory 4 representation learning 3 Learning 2 Learning process 2 Lernen 2 Lernprozess 2 Time series anomaly detection 2 attention mechanisms 2 contrastive learning 2 embeddings 2 heterogeneous networks 2 open innovation communities (OICs) 2 self-supervised representation learning 2 synthetic anomaly 2 user segmentation 2 Analytics and Data Science 1 Auslandsinvestition 1 Autoencoders 1 Betriebliche Wertschöpfung 1 Beziehungsmarketing 1 Customer Relationship Management 1 Customer Value and Value Chain 1 Customer integration 1 Customer value 1 Deep Reinforcement Learning 1 Dynamic Difficulty Adjustment 1 Dynamic Policy 1 Foreign Direct Investment 1 Foreign investment 1 Innovation management 1 Innovationsmanagement 1 Insurance 1 Insurance market 1 Insurance premium 1 Kundenintegration 1 Kundenwert 1 Latent Variable Models 1 Market segmentation 1 Marktsegmentierung 1
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Online availability
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Free 7 CC license 1
Type of publication
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Article 4 Book / Working Paper 3
Type of publication (narrower categories)
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Article in journal 3 Aufsatz in Zeitschrift 3 Working Paper 3 Arbeitspapier 2 Graue Literatur 2 Non-commercial literature 2 Article 1
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Language
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English 7
Author
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Dai, Yongsheng 2 Daradkeh, Mohammad 2 Quinn, Barry 2 Rafferty, Karen 2 Spence, Ivor 2 Wang, Hui 2 Ascarza, Eva 1 Blier-Wong, Christopher 1 Delong, Łukasz 1 Huang, Ta-Wei 1 Israeli, Ayelet 1 Kozak, Anna 1 Lamontagne, Luc 1 Ma, Liangzong 1 Marceau, Etienne 1
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Published in...
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ASTIN bulletin : the journal of the International Actuarial Association 2 Journal of Open Innovation: Technology, Market, and Complexity 1 Journal of open innovation : technology, market, and complexity 1 QBS Research Paper 1 Queen’s Management School working paper series : working paper series 1 Working papers / Harvard Business School, Division of Research 1
Source
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ECONIS (ZBW) 5 EconStor 2
Showing 1 - 7 of 7
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Dynamic personalization with multiple customer signals : multi-response state representation in reinforcement learning
Ma, Liangzong; Huang, Ta-Wei; Ascarza, Eva; Israeli, Ayelet - 2025
Persistent link: https://www.econbiz.de/10015197090
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TDSRL: Time Series Dual Self-Supervised Representation Learning for Anomaly Detection from Different Perspectives
Dai, Yongsheng; Wang, Hui; Rafferty, Karen; Spence, Ivor; … - 2024
-Supervised Representation Learning) for robust anomaly detection. TDSRL leverages synthetic anomaly segments which are artificially generated to …
Persistent link: https://www.econbiz.de/10014513943
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Cover Image
TDSRL : Time Series Dual Self-Supervised Representation Learning for anomaly detection from different perspectives
Dai, Yongsheng; Wang, Hui; Rafferty, Karen; Spence, Ivor; … - 2024
-Supervised Representation Learning) for robust anomaly detection. TDSRL leverages synthetic anomaly segments which are artificially generated to …
Persistent link: https://www.econbiz.de/10014513955
Saved in:
Cover Image
A representation-learning approach for insurance pricing with images
Blier-Wong, Christopher; Lamontagne, Luc; Marceau, Etienne - In: ASTIN bulletin : the journal of the International … 54 (2024) 2, pp. 280-309
Persistent link: https://www.econbiz.de/10015055289
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The use of autoencoders for training neural networks with mixed categorical and numerical features
Delong, Łukasz; Kozak, Anna - In: ASTIN bulletin : the journal of the International … 53 (2023) 2, pp. 213-232
Persistent link: https://www.econbiz.de/10014320194
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A user segmentation method in heterogeneous open innovation communities based on multilayer information fusion and attention mechanisms
Daradkeh, Mohammad - In: Journal of Open Innovation: Technology, Market, and … 8 (2022) 4, pp. 1-19
The heterogeneity and diversity of users and external knowledge resources is a hallmark of open innovation communities (OICs). Although user segmentation in heterogeneous OICs is a prominent and recurring issue, it has received limited attention in open innovation research and practice. Most...
Persistent link: https://www.econbiz.de/10014329686
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Cover Image
A user segmentation method in heterogeneous open innovation communities based on multilayer information fusion and attention mechanisms
Daradkeh, Mohammad - In: Journal of open innovation : technology, market, and … 8 (2022) 4, pp. 1-19
The heterogeneity and diversity of users and external knowledge resources is a hallmark of open innovation communities (OICs). Although user segmentation in heterogeneous OICs is a prominent and recurring issue, it has received limited attention in open innovation research and practice. Most...
Persistent link: https://www.econbiz.de/10013413142
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