Mochen’s Blog

Why Are Null Hypotheses Often about Equality?

causal-inference

exposition

A casual tour through hypothesis testing, p-value, and R. A. Fisher

Sequence-to-Sequence Transformer in Pytorch

machine-learning

exposition

A step-by-step demonstration

The Reading List

research

A collection of timeless classics

Lasso vs. Ridge

machine-learning

exposition

An interesting question on shrinkage methods with a graphical explanation

Common Identification Strategies and Program Evaluation

exposition

causal-inference

Connections between linear regression, IV, DID and ATE, LATE, ATT estimations

Cluster Distance in Hierarchical Clustering

exposition

machine-learning

An In-Depth Discussion of Different Linkage Methods and the Lance–Williams Algorithm

The Assumptions We Take for Granted

causal-inference

exposition

machine-learning

Two interesting questions about linear regression

Training Word Embeddings

machine-learning

exposition

A step-by-step illustration of skip-gram and continuous bag-of-words models

The Non-Collapsibility of Logistic Regressions

causal-inference

exposition

Logit regression is really weird and I had no idea

The Thing about LSTM and Exploding Gradients

machine-learning

exposition

Why LSTM addresses vanishing gradients but not exploding ones?

PDP, M-Plot, and ALE

machine-learning

exposition

A Brief Description of Three Popular Model-Agnostic Interpretation Methods

ForestIV

research

Demonstration of the ForestIV Implementation in R

A Collection of Natural Experiments and Research Opportunities

research

What happened when and what can be done

Random Stuff Cancels Out, Right?

causal-inference

exposition

The Perils of Random Measurement Error in Regression Analysis

Multicollinearity or Omitted Variable Bias? Answers to a Seeming Conundrum

causal-inference

exposition

In statistics or causal inference courses, students are usually taught a number of “threats” they need to watch out for when running regression analyses, such as…

An Intuitive Explanation of ROC and AUC

machine-learning

exposition

For students who are learning the basics of Machine Learning, one of the most challenging topics is the ROC curve and the AUC measure of a classifier. While students may be…

Bias, Discrimination, and Algorithmic Fairness

machine-learning

research

This is a (outdated) document on recent literature concerning discrimination and fairness issues in decisions driven by machine learning algorithms. A more comprehensive…