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3. Shrinkage Estimators

17 March 2021, Wednesday   statistical learning   The Elements of Statistical Learning  

As a remedy for overdetermined systems and variable selection rule, I would like to cover shrinkage methods in this section. Especially, I would like to focus on ridge and lasso penalization.
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2. Linear classifiers

16 March 2021, Tuesday   statistical learning   The Elements of Statistical Learning  

In this chapter, linear classifiers will be introduced and will be compared. Specifically, logistic regression and linear discriminant analysis will be described in detail.
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2. Univariate Kernel Density Estimation

13 March 2021, Saturday   nonparametric   kernel  

From histogram, we will start discussing nonparametric kernel methods.
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2. Explore-Then-Commit algorithm

05 March 2021, Friday   adaptive sequential decision making   bandit  

Here, we continue to describe the multi-armed bandit problem in detail. The notion of regret will be introduced. Then our first bandit algorithm, explore-then-commit (ETC) will be described.
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1. Introduction to Multi-armed Bandit

05 March 2021, Friday   adaptive sequential decision making   bandit  

The [Bandit] series of posts is my memo on the lecture Seminar in Recent Development of Applied Statistics (Spring, 2021) by Prof. Myunghee Cho Paik. This lecture focuses on adaptive sequential decision making. To be more specific, it covers wide variants of bandit problems.
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