# WeiYa's Work Yard

##### January 16, 2020

This post is based on the material of the second lecture of STAT 6050 instructed by Prof. Wicker, and mainly refer some more formally description from the book, Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar - Foundations of Machine Learning-The MIT Press (2012).

## Classification with Imperfect Training Labels

##### January 15, 2020

This post is based on the talk, given by Timothy I. Cannings at the 11th ICSA International Conference on Dec. 22th, 2019, the corresponding paper is Cannings, T. I., Fan, Y., & Samworth, R. J. (2019). Classification with imperfect training labels. ArXiv:1805.11505 [Math, Stat]

## NGS for NGS

##### January 11, 2020

This post is based on the talk, Next-Generation Statistical Methods for Association Analysis of Now-Generation Sequencing Studies, given by Dr. Xiang Zhan at the Department of Statistics and Data Science, Southern University of Science and Technology on Jan. 05, 2020.

## Concentration Inequality for Machine Learning

##### January 09, 2020

This post is based on the material of the first lecture of STAT6050 instructed by Prof. Wicker.

## DNA copy number profiling: from bulk tissue to single cells

##### January 02, 2020

This post is based on the talk given by Yuchao Jiang at the 11th ICSA International Conference on Dec. 20th, 2019.

## CEASE

##### December 20, 2019

This post is based on the Peter Hall Lecture given by Prof. Jianqing Fan at the 11th ICSA International Conference on Dec. 20th, 2019.

## Group Inference in High Dimensions

##### December 17, 2019

This post is based on the slides for the talk given by Zijian Guo at The International Statistical Conference In Memory of Professor Sik-Yum Lee

## Conditional Quantile Regression Forests

##### December 12, 2019

This note is based on the slides of the seminar, Dr. ZHU, Huichen. Conditional Quantile Random Forest.

## Quantile Regression Forests

##### December 10, 2019

This post is based on Meinshausen, N. (2006). Quantile Regression Forests. 17. since a coming seminar is related to such topic.

## Fantastic Generalization Measures and Where to Find Them

##### December 06, 2019

The post is based on Jiang, Y., Neyshabur, B., Mobahi, H., Krishnan, D., & Bengio, S. (2019). Fantastic Generalization Measures and Where to Find Them. ArXiv:1912.02178 [Cs, Stat].which was shared by one of my friend in the WeChat Moment, and then I took a quick look.

## Combining $p$-values in Meta Analysis

##### December 04, 2019

I came across the term meta-analysis in the previous post, and I had another question about nominal size while reading the paper of the previous post, which reminds me Keith’s notes. By coincidence, I also find the topic about meta-analysis in the same notes. Hence, this post is mainly based on Keith’s notes, and reproduce the power curves by myself.

## Union-intersection tests and Intersection-union tests

##### December 02, 2019

This post is based on section 8.3 of Casella and Berger (2001).

## Isotropic vs. Anisotropic

##### October 24, 2019

I came across isotropic and anisotropic covariance functions in kjytay’s blog, and then I found more materials, chapter 4 from the book Gaussian Processes for Machine Learning, via the reference in StackExchange: What is an isotropic (spherical) covariance matrix?.

## Noise Outsourcing

##### October 10, 2019

I learnt the term Noise Outsourcing in kjytay’s blog, which is based on Teh Yee Whye’s IMS Medallion Lecture at JSM 2019.

## Sub Gaussian

##### October 05, 2019

This post is based on Wainwright (2019).

## ABC for Socks

##### September 24, 2019 0 Comments

This post is based on Prof. Robert’s slides on JSM 2019 and an intuitive blog from Rasmus Bååth.