Category
Graphical models
Related lectures (47)
Latent variables in choice models: Optima case studyMOOC: Selected Topics on Discrete Choice
Explores the Optima case study, analyzing attitudes and mode choice.
Causal Discovery: Latent Variable Models
Explores causal discovery using latent variable models, emphasizing the challenges and solutions in inferring causal relationships from non-Gaussian data.
Latent Factor Analysis: Movie Genre Classification
Explores latent factor analysis for movie genre classification based on male versus female leads.
Recommender Systems: Overview and Methods
Explores the evolution of recommenders, collaborative filtering, Netflix Prize, model training, and optimization techniques.
Understanding Preference Elicitation
Explores preference elicitation, latent variables, and the impact of external events on decision-making.
Latent Space Models: Inference and Applications
Explores latent space models, network representations, spectral decompositions, and parameter estimation methods.
Factor Models: Latent Variables and Asset Pricing
Covers Factor Models, including PCA, asset pricing, factor investing, GMM, and Fama-McBeth estimation.
Belief Propagation on Graphs
Covers belief propagation on graphs, exploring computation challenges and heuristics, focusing on sparse random graphs' loop properties.
Discrete Choice Analysis
Explores the integration of machine learning into discrete choice models, emphasizing the importance of theory constraints and hybrid modeling approaches.
Variational Inference and Neural Networks
Covers variational inference and neural networks for classification tasks.