We present a tutorial on Bayesian optimization, a method of finding the maximum of expensive cost functions. Bayesian optimization employs the Bayesian technique of setting a prior over the objective function and combining it with evidence to get a posterior function. This permits a utility-based selection of the next observation to make on the objective function, which must take into account both
自分は情報幾何をこれから勉強するわけでもないのだが、メモということで。 情報理論 (ちくま学芸文庫) 情報理論の基礎―情報と学習の直観的理解のために 情報幾何学の基礎 (数理情報科学シリーズ) 別冊数理科学 情報幾何学の新展開 2014年 08月号 Information Geometry and Its Applications | Springer for Research & Development Methods of Information Geometry Differential-Geometrical Methods in Statistics | Springer for Research & Development Geometric Modeling in Probability and Statistics Information Geometry (Ergebni
On Graduated Optimization for Stochastic Non-Convex Problems Elad Hazan EHAZAN@CS.PRINCETON.EDU Princeton University Kfir Y. Levy KFIRYL@TX.TECHNION.AC.IL Technion - Israel Institute of Technology Shai Shalev-Shwartz SHAIS@CS.HUJI.AC.IL The Hebrew University of Jerusalem, Israel Abstract The graduated optimization approach, also known as the continuation method, is a pop- ular heuristic to solving
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