Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Home

Lecture

Derivation of EM for the GMM

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (51)

Data Classification: Gaussian Mixture Models Log in to Mediaspace to watch this video

Explores Gaussian Mixture Models for data classification, focusing on denoising signals and estimating original data using likelihood and posteriori approaches.

Jacamar Data Analysis Log in to Mediaspace to watch this video

Covers jacamar data analysis, smoking data models, and challenges with log-linear models in visual impairment data.

Normal Distribution: Properties and Calculations Log in to Mediaspace to watch this video

Covers the normal distribution, including its properties and calculations.

Statistical Theory: Maximum Likelihood Estimation Log in to Mediaspace to watch this video

Explores the consistency and asymptotic properties of the Maximum Likelihood Estimator, including challenges in proving its consistency and constructing MLE-like estimators.

Generalized Linear Models: A Brief Review Log in to Mediaspace to watch this video

Provides an overview of Generalized Linear Models, focusing on logistic and Poisson regression models, and their implementation in R.

Topic Models: Latent Dirichlet Allocation Log in to Mediaspace to watch this video

Covers topic models, focusing on Latent Dirichlet Allocation, clustering, GMMs, Dirichlet distribution, LDA learning, and applications in digital humanities.

Conditional Probability: Understanding Events and Their Relationships Log in to Mediaspace to watch this video

Covers conditional probability, illustrating how events influence each other's probabilities and its applications in real-world scenarios.

Harmonic Potential: Schrödinger Equation and Eigenstates Log in to Mediaspace to watch this video

Covers the Schrödinger equation, wave function normalization, and eigenstates.

Elements of Statistics: Probability and Random Variables Log in to Mediaspace to watch this video

Introduces key concepts in probability and random variables, covering statistics, distributions, and covariance.

Statistical Models and Parameter Estimation Log in to Mediaspace to watch this video

Explores statistical models, parameter estimation, and sampling distributions in probability and statistics.

Statistical Theory: Inference and Optimality Log in to Mediaspace to watch this video

Explores constructing confidence regions, inverting hypothesis tests, and the pivotal method, emphasizing the importance of likelihood methods in statistical inference.

Important Sampling: Monte Carlo Estimation Log in to Mediaspace to watch this video

Covers important sampling for efficient Monte Carlo estimation of expected values using a new distribution to reduce variance.

Clustering & Density Estimation Log in to Mediaspace to watch this video

Covers clustering, PCA, LDA, K-means, GMM, KDE, and Mean Shift algorithms for density estimation and clustering.

Decision Rules: Maximum a Posteriori Decision Log in to Mediaspace to watch this video

Explores decision rules based on likelihood ratios and the maximum a posteriori decision.

Gaussian Correlation Conjecture Log in to Mediaspace to watch this video

Explores the proof of the Gaussian correlation conjecture and its implications on random vectors and covariance matrices.

Statistics of Multivariate Extremes Log in to Mediaspace to watch this video

Covers extremal limit theorems, basic statistical analysis, and applications to multivariate extremes, emphasizing the importance of understanding the distribution of maxima.

Log-Concave Functions Log in to Mediaspace to watch this video

Covers the concept of log-concave functions and their implications in probability distributions and Gaussian correlation inequalities.

Estimating R: Marginal and Conditional Distributions Log in to Mediaspace to watch this video

Covers the estimation of R using bivariate normal distributions and explores the marginal and conditional distributions of X₁ and X₂.

Elements of Statistics: Memorylessness, Stationary Processes, Estimation using MLE Log in to Mediaspace to watch this video

Explores memorylessness in distributions, stationary processes, and estimation using MLE.

L-Moment Estimation: Probability-Weighted Moments Log in to Mediaspace to watch this video

Covers L-moment estimation, probability-weighted moments, and maximum likelihood inference basics.

Page 2 of 3