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Preference Estimation with Inconsistent Feedback: A Bayesian Approach

https://doi.org/10.2139/ssrn.5024872
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Finite Mixture Models
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A Preference-Based Recommender System
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Privacy in Recommender Systems
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The Unfairness of Active Users and Popularity Bias in Point-of-Interest Recommendation
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Humans show a higher preference for stimuli that are predictive relative to those that are predictable
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Behavioral welfare economics and risk preferences: a Bayesian approach
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Accelerated parallel non-conjugate sampling for Bayesian non-parametric models
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Likelihood estimation of consumer preferences in choice-based conjoint analysis
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Data-based prediction under uncertainty: CDF-quantile distributions and info-gap robustness
inferredcites →https://doi.org/10.1016/j.jocm.2020.100229openalex-snapshot
A Dirichlet process mixture model of discrete choice: Comparisons and a case study on preferences for shared automated vehicles
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Parallel approaches to machine learning—A comprehensive survey
inferredcites →https://doi.org/10.1016/j.knosys.2020.106434openalex-snapshot
TrustTF: A tensor factorization model using user trust and implicit feedback for context-aware recommender systems
inferredcites →https://doi.org/10.1080/03772063.2021.1997357openalex-snapshot
Matrix Factorization in Recommender Systems: Algorithms, Applications, and Peculiar Challenges
inferredcites →https://doi.org/10.1109/34.990138openalex-snapshot
Unsupervised learning of finite mixture models
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Decision analysis: Perspectives on inference, decision, and experimentation
inferredcites →https://doi.org/10.1109/tlt.2012.11openalex-snapshot
Context-Aware Recommender Systems for Learning: A Survey and Future Challenges
inferredcites →https://doi.org/10.1109/wi.2016.0036openalex-snapshot
Recommendation System Based on Prediction of User Preference Changes
inferredcites →https://doi.org/10.1111/ajae.12257openalex-snapshot
Nonparametric segmentation methods: Applications of unsupervised machine learning and revealed preference
inferredcites →https://doi.org/10.1111/j.0006-341x.1999.00463.xopenalex-snapshot
Finite Mixture Modeling with Mixture Outcomes Using the EM Algorithm
inferredcites →https://doi.org/10.1145/2488388.2488457openalex-snapshot
SoCo
inferredcites →https://doi.org/10.1145/2911451.2911489openalex-snapshot
Fast Matrix Factorization for Online Recommendation with Implicit Feedback
inferredcites →https://doi.org/10.1145/3341981.3344225openalex-snapshot
Unifying Explicit and Implicit Feedback for Rating Prediction and Ranking Recommendation Tasks
inferredcites →https://doi.org/10.1145/3373807openalex-snapshot
Efficient Neural Matrix Factorization without Sampling for Recommendation
inferredcites →https://doi.org/10.1145/3383313.3412488openalex-snapshot
Neural Collaborative Filtering vs. Matrix Factorization Revisited
inferredcites →https://doi.org/10.1201/9781003007210-8openalex-snapshot
Collaborative Filtering in Recommender Systems: Technicalities, Challenges, Applications, and Research Trends
inferredcites →https://doi.org/10.1257/jel.20161148openalex-snapshot
Estimating Risk Preferences in the Field
inferredcites →https://doi.org/10.1257/mic.20150216openalex-snapshot
Mutually Consistent Revealed Preference Demand Predictions
inferredcites →https://doi.org/10.3386/w27685openalex-snapshot
Behavioral Welfare Economics and Risk Preferences: A Bayesian Approach
inferredcites →https://doi.org/10.3758/s13423-014-0684-4openalex-snapshot
Using Bayesian hierarchical parameter estimation to assess the generalizability of cognitive models of choice
inferredcites →https://doi.org/10.5281/zenodo.8002437openalex-snapshot
A Review of Bayesian Machine Learning Principles, Methods, and Applications
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