Latent variables in choice models: Optima case study

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Latent Space Models: Inference and Applications

Explores latent space models, network representations, spectral decompositions, and parameter estimation methods.

Statistical Analysis of Networks: Link Prediction and Biclustering

Explores link prediction, logistic regression, causal inference, and biclustering in statistical network analysis.

Recommender Systems and Structure Discovery

Explores recommender systems, latent factor models, and clustering algorithms for structure discovery.

Latent Variable Models

Explores latent variable models, EM algorithm, and Jensen's inequality in statistical modeling.

Beyond Rationality: Behavioral Economics

Delves into human decision-making beyond rationality, exploring concepts like the decoy effect.

Choice Models: Predicting Consumer Behavior

Explores choice models to predict consumer behavior and market shares.

Variational Inference and Neural Networks

Covers variational inference and neural networks for classification tasks.

Outlier Analysis

Discusses predicting future behavior and analyzing outliers in choice models.

Learning Latent Models in Graphical Structures

Explores learning latent models in graphical structures, focusing on scenarios with incomplete samples and introducing the notion of distance among variables.

Choice Theory: Theoretical Foundations

Covers the theoretical foundations of choice theory, decision makers, alternatives, attributes, decision rules, utility, and behavioral assumptions.