The 41st In Silico Megabank Research Seminar will be held on Tuesday, December 10.<\/p>\n
This Time, we will be welcoming Dr. Yu Nishiyama, The Institute of Statistical Mathematics as our lecturer, and he will be speaking on \u201cTopic of Bayesian Inference Using Positive Definite Kernel as the Most Recent Kernel Method.\u201d<\/p>\n
\u30fbDate\/Time: December 10 (Tue.) 17:00\u201018:30
\n\u30fbVenue: Middle Conference Room (2nd Floor), Building #1, Tohoku University School of Medicine
\n\u30fbTitle: Topic of Bayesian Inference Using Positive Definite Kernel as the Most Recent Kernel Method
\n\u30fbLecturer: Yu Nishiyama ( The Institute of Statistical Mathematics)<\/p>\n
\uff0aThis lecture is transferable as a class in the medical research-related lecture course.<\/p>\n
\u30fbAbstract: In recent studies regarding Kernel Method, Bayesian inference using positive definite Kernel (Kernel Bayes\u2019 Rule) is examined. This methodology reasons with a kernel mean setting forth a consistency rate instead of probability distribution. The kernel mean is defined with an average in the feature space rather than regular average of probability distribution.\u00a0 In this study, we will introduce kernelized version of both \u201cSum rule\u201d used for marginalization and \u201cBayes\u2019 rule\u201d producing Bayesian Posterior Distribution known as \u201cKernel Sum Rule\u201d and \u201cKernel Bayes\u2019 Rules.\u201d Combination of these two rules results in filtering of state special model and reinforcement learning algorithm. Kernel Bayes\u2019 Rule which is the combined form of probability models performed by the presenters recently is also introduced.<\/p>\n
\u30fbOrganizer : Kaname Kojima, Masao Nagasaki<\/p>\n","protected":false},"excerpt":{"rendered":"
The 41st In Silico Megabank Research Seminar will be held on Tuesday, December 10. This Time, we will be welcoming Dr. Yu Nishiyama, The Institute of Statistical Mathematics as our lecturer, and he will be speaking on \u201cTopic of Bayesian … Continue reading