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[Write to Learn] Minimal Description Length and Kolmogorov Complexity

[Write to Learn] Minimal Description Length and Kolmogorov Complexity

Recently, the concept of compression and learning has piqued my interest, as discussed in a previous blog post. To explore this further, I've chosen to delve into Peter Grünwald's tutorial note, "A Tutorial Introduction to the Minimal Description Length Principle," with the intention of

Learning <=> Compression <=> Prediction

Learning <=> Compression <=> Prediction

Introduction Occasionally, I will contemplate the meaning of learning. I learned very early that learning is not memorisation. One of the reasons is that I hate memorising facts without understanding them. Also, thanks to the Hong Kong education system, there is no need to memorise many facts as equations and

[Book Summary] Guns, Germs, and Steel--From Food to Guns, Germs, and Steel

[Book Summary] Guns, Germs, and Steel--From Food to Guns, Germs, and Steel

The Core Arguments * When the human population became sufficiently large and dense, and the rise of livestock and agriculture led to the development of infectious diseases, the spread of these diseases became a significant factor in human history. * Early writing served the needs of political institutions. It was never developed

[Book Summary] Guns, Germs, and Steel--The Rise and Spread of Food Production

[Book Summary] Guns, Germs, and Steel--The Rise and Spread of Food Production

The Core Arguments * Domestication as a Driver of Development: Jared Diamond posits that the availability of domesticable plants and animals is the key factor explaining disparities in human development. * Global Patterns of Food Production: Food production emerged independently in several regions, including the Fertile Crescent, China, Mesoamerica, the Andes, and

Credit Risk Modeling with Transformers: A Literature Review and My Experimentation

Credit Risk Modeling with Transformers: A Literature Review and My Experimentation

1. Babaei and Giudici (2024) - "GPT Classifications, with Application to Credit Lending" Technique: Prompt-engineering Focus: * Application of GPT models in binary classification for credit scoring. * Comparison with traditional machine learning models like logistic regression. Key Points: a. Data Preparation and Input for Transformer Models: * The prompt sent

Using Large Language Models in Classification Tasks: A Case Study in Credit Risk Modeling-- My Failed Attempt #1

Using Large Language Models in Classification Tasks: A Case Study in Credit Risk Modeling-- My Failed Attempt #1

With the advancement of large language models, I am curious about their implications for the industry practice of classification tasks, where traditional models like logistic regression and tree-based models currently dominate. The data I used comes from Kaggle, specifically from a competition organised by Home Credit, a prominent player in

[Book Summary] Guns, Germs, and Steel--The Rise and Spread of Food Production (Part 1)

[Book Summary] Guns, Germs, and Steel--The Rise and Spread of Food Production (Part 1)

In this blog, I will first briefly summarise part 2 of the book since I have been occupied with my other commitments. The first two chapters describe the problem the author intends to solve in the next five chapters. The Core Arguments * The author argues that the availability of domestic