Reasoning Under Uncertainty: Towards Collaborative Interactive Machine Learning

S. Robert, S. Büttner, C. Röcker, A. Holzinger, in: A. Holzinger (Ed.), Machine Learning for Health Informatics : State-of-the-Art and Future Challenges , Springer, Cham, CH, 2016, pp. 357–376.

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Sammelwerk - Beitrag | Veröffentlicht | Englisch
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Abstract
In this paper, we present the current state-of-the-art of decision making (DM) and machine learning (ML) and bridge the two research domains to create an integrated approach of complex problem solving based on human and computational agents. We present a novel classification of ML, emphasizing the human-in-the-loop in interactive ML (iML) and more specific on collaborative interactive ML (ciML), which we understand as a deep integrated version of iML, where humans and algorithms work hand in hand to solve complex problems. Both humans and computers have specific strengths and weaknesses and integrating humans into machine learning processes might be a very efficient way for tackling problems. This approach bears immense research potential for various domains, e.g., in health informatics or in industrial applications. We outline open questions and name future challenges that have to be addressed by the research community to enable the use of collaborative interactive machine learning for problem solving in a large scale.
Erscheinungsjahr
Buchtitel
Machine Learning for Health Informatics : State-of-the-Art and Future Challenges
Band
9605
Seite
357-376
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Robert S, Büttner S, Röcker C, Holzinger A. Reasoning Under Uncertainty: Towards Collaborative Interactive Machine Learning. In: Holzinger A, ed. Machine Learning for Health Informatics : State-of-the-Art and Future Challenges . Vol 9605. Lecture Notes in Computer Science /  Lecture Notes in Artificial Intelligence . Cham, CH: Springer; 2016:357-376. doi:10.1007/978-3-319-50478-0_18
Robert, S., Büttner, S., Röcker, C., & Holzinger, A. (2016). Reasoning Under Uncertainty: Towards Collaborative Interactive Machine Learning. In A. Holzinger (Ed.), Machine Learning for Health Informatics : State-of-the-Art and Future Challenges (Vol. 9605, pp. 357–376). Cham, CH: Springer. https://doi.org/10.1007/978-3-319-50478-0_18
Robert S et al. (2016) Reasoning Under Uncertainty: Towards Collaborative Interactive Machine Learning. In Holzinger A (ed.), Machine Learning for Health Informatics : State-of-the-Art and Future Challenges , vol. 9605. Cham, CH: Springer, pp. 357–376.
Robert, Sebastian, Sebastian Büttner, Carsten Röcker, and Andreas Holzinger. “Reasoning Under Uncertainty: Towards Collaborative Interactive Machine Learning.” In Machine Learning for Health Informatics : State-of-the-Art and Future Challenges , edited by Andreas Holzinger, 9605:357–76. Lecture Notes in Computer Science /  Lecture Notes in Artificial Intelligence . Cham, CH: Springer, 2016. https://doi.org/10.1007/978-3-319-50478-0_18.
Robert, Sebastian, Sebastian Büttner, Carsten Röcker und Andreas Holzinger. 2016. Reasoning Under Uncertainty: Towards Collaborative Interactive Machine Learning. In: Machine Learning for Health Informatics : State-of-the-Art and Future Challenges , hg. von Andreas Holzinger, 9605:357–376. Lecture Notes in Computer Science /  Lecture Notes in Artificial Intelligence . Cham, CH: Springer. doi:10.1007/978-3-319-50478-0_18, .
Robert, Sebastian ; Büttner, Sebastian ; Röcker, Carsten ; Holzinger, Andreas: Reasoning Under Uncertainty: Towards Collaborative Interactive Machine Learning. In: Holzinger, A. (Hrsg.): Machine Learning for Health Informatics : State-of-the-Art and Future Challenges , Lecture Notes in Computer Science /  Lecture Notes in Artificial Intelligence . Bd. 9605. Cham, CH : Springer, 2016, S. 357–376
S. Robert, S. Büttner, C. Röcker, A. Holzinger, Reasoning Under Uncertainty: Towards Collaborative Interactive Machine Learning, in: A. Holzinger (Ed.), Machine Learning for Health Informatics : State-of-the-Art and Future Challenges , Springer, Cham, CH, 2016: pp. 357–376.
S. Robert, S. Büttner, C. Röcker, and A. Holzinger, “Reasoning Under Uncertainty: Towards Collaborative Interactive Machine Learning,” in Machine Learning for Health Informatics : State-of-the-Art and Future Challenges , vol. 9605, A. Holzinger, Ed. Cham, CH: Springer, 2016, pp. 357–376.
Robert, Sebastian, et al. “Reasoning Under Uncertainty: Towards Collaborative Interactive Machine Learning.” Machine Learning for Health Informatics : State-of-the-Art and Future Challenges , edited by Andreas Holzinger, vol. 9605, Springer, 2016, pp. 357–76, doi:10.1007/978-3-319-50478-0_18.
Robert, Sebastian et. al. (2016): Reasoning Under Uncertainty: Towards Collaborative Interactive Machine Learning, in: Andreas Holzinger (Hg.): Machine Learning for Health Informatics : State-of-the-Art and Future Challenges (=Lecture Notes in Computer Science /  Lecture Notes in Artificial Intelligence 9605), Cham, CH, S. 357–376.
Robert S, Büttner S, Röcker C, Holzinger A. Reasoning Under Uncertainty: Towards Collaborative Interactive Machine Learning. In: Holzinger A, editor. Machine Learning for Health Informatics : State-of-the-Art and Future Challenges . Cham, CH: Springer; 2016. p. 357–76. (Lecture Notes in Computer Science /  Lecture Notes in Artificial Intelligence ; vol. 9605).

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