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References from A tutorial on learning from preferences and choices with Gaussian processes. Local targets link to admitted publications; unresolved targets remain external evidence.
A generalized additive model for discrete-choice data
10.1080/07350015.1999.10524817 · 1999 · External reference
Looping in the human: collaborative and explainable Bayesian optimization
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Accelerated spectral ranking
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Gaussian process regression with skewed errors
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Bayesian conjugacy in probit, Tobit, multinomial probit and extensions: a review and new results
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On the unification of families of skew-Normal distributions
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Pareto rationalizability by two single peaked preferences
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Linearly constrained Gaussian processes are SkewGPs: application to monotonic preference learning and desirability
2024 · External reference
Unresolved reference
External reference
Skew Gaussian processes for classification
10.1007/s10994-020-05906-3 · 2020 · External reference
A unified framework for closed-form nonparametric regression, classification, preference and mixed problems with Skew Gaussian processes
10.1007/s10994-021-06039-x · 2021 · External reference
Preferential Bayesian optimisation with skew Gaussian processes
2021 · External reference
Bayesian optimization for choice data
2023 · External reference
Learning choice functions with Gaussian processes
2023 · External reference
A Bayesian Wilcoxon signed-rank test based on the Dirichlet process
2014 · External reference
A discrete choice model for subset selection
2018 · External reference
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External reference
The normal law under linear restrictions: simulation and estimation via minimax tilting
10.1111/rssb.12162 · 2017 · External reference
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Constraint-based optimization and utility elicitation using the minimax decision criterion
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Learning to rank using gradient descent
2005 · External reference
Learning to rank: from pairwise approach to listwise approach
2007 · External reference
When do noisy votes reveal the truth?
10.1145/2892565 · 2016 · External reference
Efficient Bayesian inference for generalized Bradley–Terry models
10.1080/10618600.2012.638220 · 2012 · External reference
Learning inconsistent preferences with Gaussian processes
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Deep reinforcement learning from human preferences
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10.18637/jss.v095.i11 · 2020 · External reference
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2019 · External reference
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1954 · External reference
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Conjugate Bayes for probit regression via unified skew-normal distributions
10.1093/biomet/asz034 · 2019 · External reference
Indifference or indecisiveness? Choice theoretic foundations of incomplete preferences
10.1016/j.geb.2005.06.007 · 2006 · External reference
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Generalized robust conjoint estimation
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2000 · External reference
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10.1002/jae.1223 · 2012 · External reference
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GPyTorch: Blackbox matrix-matrix Gaussian process inference with GPU acceleration
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Integrals over Gaussians under linear domain constraints
2020 · External reference
Variational Gaussian process classifiers
10.1109/72.883477 · 2000 · External reference
Preferential Bayesian optimization
2017 · External reference
Bayesian inference for Plackett-Luce ranking models
2009 · External reference
10.1007/3-540-36169-3_29
10.1007/3-540-36169-3_29 · 2002 · External reference
The MovieLens datasets: history and context
2015 · External reference
Gaussian processes for big data
2013 · External reference
Scalable variational Gaussian process classification
2015 · External reference
Learning preference relations for information retrieval
1998 · External reference
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Scalable Gaussian process classification via expectation propagation
2016 · External reference
Apollo: a flexible, powerful and customisable freeware package for choice model estimation and application
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Label ranking by learning pairwise preferences
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MM algorithms for generalized Bradley-Terry models
10.1214/aos/1079120141 · 2004 · External reference
Semiparametric multinomial logit models for analysing consumer choice behaviour
10.1007/s10182-007-0033-2 · 2007 · External reference
Gibbs sampling approach for generation of truncated multivariate Gaussian random variables
1999 · External reference
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Estimation of discrete choice models with hybrid stochastic adaptive batch size algorithms
10.1016/j.jocm.2020.100226 · 2021 · External reference
Learning to rank for information retrieval
10.1561/1500000016 · 2009 · External reference
Antithetic and Monte Carlo kernel estimators for partial rankings
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Semiorders and a theory of utility discrimination
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Advanced conjoint analysis using feature selection via support vector machines
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Non-null ranking models. I
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Consensus ranking under the exponential model
2007 · External reference
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Choice functions over a finite set: a summary
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Elliptical slice sampling
2010 · External reference
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Top-k ranking Bayesian optimization
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Curve fitting and optimal design for prediction
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The variational Gaussian approximation revisited
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Training language models to follow instructions with human feedback
2022 · External reference
Learning intransitive reciprocal relations with kernel methods
10.1016/j.ejor.2010.03.018 · 2010 · External reference
Exact Hamiltonian Monte Carlo for truncated multivariate Gaussians
10.1080/10618600.2013.788448 · 2014 · External reference
Learning choice functions via Pareto-Embeddings
2020 · External reference
Learning context-dependent choice functions
10.1016/j.ijar.2021.10.002 · 2022 · External reference
The analysis of permutations
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A unifying view of sparse approximate Gaussian process regression
2005 · External reference
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The diffusion decision model: theory and data for two-choice decision tasks
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2009 · External reference
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Recursive estimation for sparse Gaussian process regression
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Correlated product of experts for sparse Gaussian process regression
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Coherent choice functions under uncertainty
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Choice functions and revealed preference
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The nontransitive consumer
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Estimation from pairwise comparisons: sharp minimax bounds with topology dependence
2015 · External reference
Taking the human out of the loop: a review of Bayesian optimization
10.1109/jproc.2015.2494218 · 2015 · External reference
Enhancing discrete choice models with representation learning
10.1016/j.trb.2020.08.006 · 2020 · External reference
Preferential batch Bayesian optimization
2021 · External reference
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Discussion of professor Ross’s paper
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Learning to summarize with human feedback
2020 · External reference
Towards practical preferential Bayesian optimization with skew Gaussian processes
2023 · External reference
RestrictedMVN: multivariate normal restricted by affine constraints
2016 · External reference
A law of comparative judgment
10.1037/h0070288 · 1927 · External reference
Variational learning of inducing variables in sparse Gaussian processes
2009 · External reference
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A note on the temporal sure preference principle and the updating of lower previsions
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Context-dependent preferences
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Coherent choice functions, desirability and indifference
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A survey of preference-based reinforcement learning methods
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A bi-partite generative model framework for analyzing and simulating large scale multiple discrete continuous travel behaviour data
10.1016/j.trc.2019.11.022 · 2020 · External reference
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