# Note

These are lecture notes I took at the University of Michigan. If you're interested in the $\LaTeX$ code, have a look on GitHub. If you're interested in my setup, also have a look on this GitHub repo or just here.

## What's in here?

All notes are written in modern style $\LaTeX$ with clear definition/theorem references and hyperlinks. Also, the drawing is done professionally and cleanly.

## Junior

### Fall 2021

#### Linear Programming (MATH561/IOE510/TO518 @Umich)

This is the first course in the series of graduate-level, large-scale and rigorous mathematical programming courses taught by Jon Lee. Topics include **Linear Programming**, **Weak and Strong Duality**, **Simplex Algorithm**, **Large-Scale Linear Programming**, **Sensitivity Analysis**, and also **Integer Programming** and their applications.

#### Analysis of Social Networks (EECS544/EECS444 @Umich)

This is a graduated level course about social network analysis taught by Vijay G Subramanian, covering topics across **Graph Partitioning Algorithm**, **Community Detection Algorithm**, **Stochastic Process and Markov Chain**, **Monte Carlo Algorithm**, **Random Graph Theory** and **Game Theory** with **Auctions and Matching Market**.

### Winter 2022

#### Algebraic Topology (MATH592 @Umich)

This is a graduate-level course taught by Jennifer Wilson about Introduction to Algebraic Topology. It is self-contained enough that only requires a background in abstract algebra and some point set topology. Topics include **CW-Complex**, **Fundamental Group**, **Van-Kampen Theorem**, **Homology**, and also their applications like Lefschetz fixed-point theorem.

#### Real Analysis (MATH597 @Umich)

This is the graduate-level Real Analysis focused on measure theory taught by Jinho Baik. Everything is built up from Measure Theory, like integration and differentiation. Topics include **Measure Theory**, **Hilbert/Banach Spaces**, **$L^p$ Spaces**, and some **Fourier analysis**.

## Senior

### Fall 2022^{1}

#### Approximation Algorithms and Hardness of Approximation (EECS598-001 @Umich)

This is the graduate-level algorithm course taught by Euiwoong Lee.

#### Functional Analysis (MATH602 @Umich)

This is the graduate-level real analysis course focused on functional analysis taught by Joseph Conlon.

- Turns out that MATH663/IOE611 Nonlinear Programming provides nice lecture slides so I wont bother scribing it myself.↩