Epistemic Uncertainty in Artificial Intelligence [electronic resource] : First International Workshop, Epi UAI 2023, Pittsburgh, PA, USA, August 4, 2023, Revised Selected Papers / edited by Fabio Cuzzolin, Maryam Sultana.
Contributor(s): Cuzzolin, Fabio [editor.] | Sultana, Maryam [editor.] | SpringerLink (Online service).
Material type: BookSeries: Lecture Notes in Artificial Intelligence: 14523Publisher: Cham : Springer Nature Switzerland : Imprint: Springer, 2024Edition: 1st ed. 2024.Description: XXVII, 113 p. 32 illus., 31 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783031579639.Subject(s): Artificial intelligence | Artificial IntelligenceAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online In: Springer Nature eBookSummary: This LNCS 14523 conference volume constitutes the proceedings of the First International Workshop, Epi UAI 2023, in Pittsburgh, PA, USA, August 2023. The 8 full papers together included in this volume were carefully reviewed and selected from 16 submissions. Epistemic AI focuses, in particular, on some of the most important areas of machine learning: unsupervised learning, supervised learning, and reinforcement learning.No physical items for this record
This LNCS 14523 conference volume constitutes the proceedings of the First International Workshop, Epi UAI 2023, in Pittsburgh, PA, USA, August 2023. The 8 full papers together included in this volume were carefully reviewed and selected from 16 submissions. Epistemic AI focuses, in particular, on some of the most important areas of machine learning: unsupervised learning, supervised learning, and reinforcement learning.
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