PRML 3.3.3-3.4 ベイズ線形回帰とモデル選択 / Baysian Linear Regression and Model Comparison)
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PRML 3.3.3-3.4 ベイズ線形回帰とモデル選択 / Baysian Linear Regression and Model Comparison)
Documentation for GPML Matlab Code version 4.2 1) What? The code provided here originally demonstrated the main algorithms from Rasmussen and Williams: Gaussian Processes for Machine Learning. It has since grown to allow more likelihood functions, further inference methods and a flexible framework for specifying GPs. Other GP packages can be found here. The code is written by Carl Edward Rasmussen
Kingman's coalescent emerging from a Wright-Fisher model. Note also the connection with perfect sampling. General Instructor: Alexandre Bouchard-Côté Check latest updates: [HTML][RSS] Dates: February 28 - April 6, 2011 Time: MW 13:30 - 15:00 Place: LSK 301 Don't hesistate to contact me if you have questions: bouchard AT stat.ubc.ca Next office hour: Wednesday, 3/30, 3:00-4:00, at LSK 330 Template
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