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Data-driven preference learning methods for value-driven multiple criteria sorting with interacting criteria
Liu, Jiapeng; Kadziński, Miłosz; Liao, Xiuwu; Mao, Xiaoxin - In: INFORMS journal on computing : JOC 33 (2021) 2, pp. 586-606
Persistent link: https://www.econbiz.de/10012546132
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Bayesian ordinal regression for multiple criteria choice and ranking
Ru, Zice; Liu, Jiapeng; Kadziński, Miłosz; Liao, Xiuwu - In: European journal of operational research : EJOR 299 (2022) 2, pp. 600-620
Persistent link: https://www.econbiz.de/10013207146
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A preference learning framework for multiple criteria sorting with diverse additive value models and valued assignment examples
Liu, Jiapeng; Kadziński, Miłosz; Liao, Xiuwu; Mao, Xiaoxin - In: European journal of operational research : EJOR 286 (2020) 3, pp. 963-985
Persistent link: https://www.econbiz.de/10012291605
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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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Probabilistic ordinal regression methods for multiple criteria sorting admitting certain and uncertain preferences
Ru, Zice; Liu, Jiapeng; Kadziński, Miłosz; Liao, Xiuwu - In: European journal of operational research : EJOR 311 (2023) 2, pp. 596-616
Persistent link: https://www.econbiz.de/10014336733