|
Graphical Models Seminar |
| 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 |