Graphical Models Seminar


Learning in Graphical Models

Michael I. Jordan (Editor)




DATE TITLE Speaker
11/1(월) A Tutorial on Learning with Bayesian Networks K. Hwang
11/3(수) Introduction to Inference for Bayesian Networks S. Kim
11/8(월) An Introduction to Variational Methods for Graphical Models S. Park
11/10(수) Improving the Mean Field Approximation Via the Use of Mixture Distributions J. Lee
11/10(수) Introduction to Monte Carlo Methods J. Oh
11/15(월) Suppressing Random Walks in Markov Chain Monte Carlo using Ordered Overrelaxation J. Chang
11/15(월) A View of the EM Algorithm that Justifies Incremental, Sparse, and Other Variations K. Hwang
11/17(수) Latent Variable Models J. Oh
11/17(수) Stochastic Algorithms for Exploratory Data Analysis: Data Clustering and Data Visualization J. Lee
11/22(월) A Hierarchical Community of Experts J. Chang
11/24(수) A Mean Field Learning Algorithm for Unsupervised Neural Networks S. Kim
11/24(수) Prediction with Gaussian Processes: From Linear Regression to Linear Prediction and Beyond S. Park