Probabilistic Preference Modeling
Probabilistic Preference Modeling is a preference modeling framework that characterizes uncertain or stochastic user preferences through probability distributions over preference relations, distinguishing itself from deterministic models by explicitly accounting for variability, inconsistency, or confidence in individual choices.
120
Publications
5.8K
Citations
277
Authors
162
Institutions
Publications per year
2017–2026
38
Parents
120
Preference learning with Gaussian processes
Wei Chu, Zoubin Ghahramani · 2005 · 362 citations
Consistency-based risk assessment with probabilistic linguistic preference relation
Yixin Zhang, Zeshui Xu, Hai Wang et al. · Applied Soft Computing · 2016 · 337 citations
Testing Different Stochastic Specificationsof Risky Choice
Graham Loomes, Robert Sugden · Economica · 1998 · 217 citations
1–5 of 120
277
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University of Illinois Urbana-Champaign, United States
4 publications · 196 citations
4
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3
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3
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1–5 of 277
162

Sichuan University
Chengdu, China
8 h-index
17 publications
1.8K citations
Singapore Management University
Singapore, Singapore
3 h-index
3 publications
120 citations

Centre National de la Recherche Scientifique
Paris, France
3 h-index
3 publications
103 citations

Minzu University of China
Beijing, China
3 h-index
7 publications
151 citations

UNSW Sydney
Sydney, Australia
3 h-index
3 publications
75 citations

University of Toronto
Toronto, Canada
3 h-index
5 publications
232 citations

Southeast University
Nanjing, China
3 h-index
5 publications
576 citations

Data61
Sydney, Australia
3 h-index
3 publications
75 citations
1–8 of 162
6 publications · 304 citations
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5 publications · 105 citations
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4 publications · 102 citations
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4 publications · 183 citations
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Repository · 4 publications · 118 citations
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