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Modeling user choice behavior under data corruption: Robust learning of the latent decision threshold model
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Modeling user choice behavior under data corruption: Robust learning of the latent decision threshold model (2023)Modeling user choice behavior under data …A deep inverse reinforcement learning approach to route choice modeling with context-dependent rewards (2023)A deep inverse reinforcement …Linking Mode Choice with Travel Behavior by Using Logit Model Based on Utility Function (2021)Linking Mode Choice with Trav…Managing bottleneck congestion with incentives (2020)Managing bottleneck congestio…Personalized incentives for promoting sustainable travel behaviors (2019)Personalized incentives for p…Robust Classification (2018)Robust ClassificationMachine learning or discrete choice models for car ownership demand estimation and prediction? (2017)Machine learning or discrete …Inverse discrete choice modelling: theoretical and practical considerations for imputing respondent attributes from the patterns of observed choices (2017)Inverse discrete choice model…Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud (2016)Fake It Till You Make It: Rep…Ignorance or integration: the cognitive processes underlying choice behavior (2009)Ignorance or integration: the…Game theory, maximum entropy, minimum discrepancy and robust Bayesian decision theory (2004)Game theory, maximum entropy,…Zur Theorie der Gesellschaftsspiele (1928)Rational Decisions (1952)On a Measure of the Information Provided by an Experiment (1956)A Contrast Between two Decision Rules for use with (Convex) Sets of Probabilities: Γ-Maximin Versus E-Admissibilty (2004)Strictly Proper Scoring Rules, Prediction, and Estimation (2007)Accuracy and the Laws of Credence (2016)Prospect Theory: An Analysis of Decision under Risk (1979)Prospect theory: An analysis of decision under risk (1988)Advances in prospect theory: Cumulative representation of uncertainty (1992)Reconsidering “evidence” for fast-and-frugal heuristics (2010)Is making a risky choice based on a weighting and adding process? 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this work references cited by second hop

References

  • 2016Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud1,264 cited
  • 2004Game theory, maximum entropy, minimum discrepancy and robust Bayesian decision theory455 cited
  • 2023A deep inverse reinforcement learning approach to route choice modeling with context-dependent rewards89 cited
  • 2009Ignorance or integration: the cognitive processes underlying choice behavior74 cited
  • 2018Robust Classification72 cited
  • 2021Linking Mode Choice with Travel Behavior by Using Logit Model Based on Utility Function71 cited
  • 2019Personalized incentives for promoting sustainable travel behaviors55 cited
  • 2017Machine learning or discrete choice models for car ownership demand estimation and prediction?54 cited
  • 2020Managing bottleneck congestion with incentives42 cited
  • 2017Inverse discrete choice modelling: theoretical and practical considerations for imputing respondent attributes from the patterns of observed choices11 cited

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