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Preference disaggregation within the regularization framework for sorting problems with multiple potentially non-monotonic criteria
Liu, Jiapeng; Liao, Xiuwu; Kadziński, Miłosz; … - In: European journal of operational research : EJOR 276 (2019) 3, pp. 1071-1089
Persistent link: https://www.econbiz.de/10012003712
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Modeling contingent decision behavior : a Bayesian nonparametric preference-learning approach
Liu, Jiapeng; Kadziński, Miłosz; Liao, Xiuwu - In: INFORMS journal on computing : JOC ; charting new … 35 (2023) 4, pp. 764-785
Persistent link: https://www.econbiz.de/10014328073
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Toward efficient ensemble learning with structure constraints : convergent algorithms and applications
Lin, Shao-Bo; Tang, Shaojie; Wang, Yao; Wang, Di - In: INFORMS journal on computing : JOC ; charting new … 34 (2022) 6, pp. 3096-3116
Persistent link: https://www.econbiz.de/10014326625
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Active learning strategies for interactive elicitation of assignment examples for threshold-based multiple criteria sorting
Kadziński, Miłosz; Ciomek, Krzysztof - In: European journal of operational research : EJOR 293 (2021) 2, pp. 658-680
Persistent link: https://www.econbiz.de/10012513246
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Deep preference learning for multiple criteria decision analysis
Martyn, Krzysztof; Kadziński, Miłosz - In: European journal of operational research : EJOR 305 (2023) 2, pp. 781-805
Persistent link: https://www.econbiz.de/10013479307
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An active preference learning approach to aid the selection of validators in blockchain environments
Gehrlein, Jonas; Miebs, Grzegorz; Brunelli, Matteo; … - In: Omega : the international journal of management science 118 (2023), pp. 1-16
Persistent link: https://www.econbiz.de/10014444375