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Related lectures (23)

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ARCH and GARCH Models

Explores ARCH and GARCH models, volatility clustering, time series, estimation, and filtering steps in financial and macroeconomic contexts.

The Topological Künneth Theorem

Explores the topological Künneth Theorem, emphasizing commutativity and homotopy equivalence in chain complexes.

Recommender Systems and Structure Discovery

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

Debiased Whittle Likelihood: Time Series and Spatial Data

Explores the Debiased Whittle likelihood for time series and spatial data, focusing on fitting spectral density to the periodogram for better predictions and parameter estimation.

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.

Introduction to ML for Behavioral Data

Covers machine learning approaches for personalization and their real-world application, emphasizing homework, projects, and feedback.

Static Analysis: Modeling Structural Behavior

Covers static analysis and the importance of accurate structural modeling in engineering.

Mixture models: summary

Summarizes mixtures of logit models, covering various mixing methods and modeling techniques for taste heterogeneity.

Sampling: Weighted Exogenous Maximum Likelihood Estimation

Introduces the Weighted Exogenous Maximum Likelihood Estimator in discrete choice models.

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