Lecture

Mixture models: alternative specific variance

Related lectures (37)
Common Distributions: Moment Generating Functions
Explores common probability distributions, special distributions, and entropy concepts.
Discrete Choice Analysis
Introduces Discrete Choice Analysis, covering scale, depth, data collection, and statistical inference.
Estimation Methods
Covers various methods for estimating model parameters, such as method of moments and maximum likelihood estimation.
Bayesian Estimation: Overview and Examples
Introduces Bayesian estimation, covering classical versus Bayesian inference, conjugate priors, MCMC methods, and practical examples like temperature estimation and choice modeling.
Bayesian Inference: Gaussian Variables
Explores Bayesian inference for Gaussian random variables, covering joint distribution, marginal pdfs, and the Bayes classifier.
Gaussian Mixture Models: Data Classification
Explores denoising signals with Gaussian mixture models and EM algorithm, EMG signal analysis, and image segmentation using Markovian models.
Generalized Linear Regression: Classification
Explores Generalized Linear Regression, Classification, confusion matrices, ROC curves, and noise in data.
Elements of Statistics: Probability, Distributions, and Estimation
Covers probability theory, distributions, and estimation in statistics, emphasizing accuracy, precision, and resolution of measurements.
Interval Estimation: Method of Moments
Covers the method of moments for estimating parameters and constructing confidence intervals based on empirical moments matching distribution moments.
Weighted Least Squares Estimation: IRLS Algorithm
Explores the IRLS algorithm for weighted least squares estimation in GLM.

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.