Hello! We are organizing a Machine Learning Reading Seminar at the math department of Texas State University to learn about the mathematical foundation of this technology and their rapidly expanding use in our world.
The Machine Learning Reading Seminar will meet every other Friday in Fall 2023 starting from 9/22 from 11am-12pm in Derrick 328. All interested faculty, staff, and undergraduate and graduate students are welcome.
Contact Christine Lee at vne11@txstate.edu if you are interested in receiving seminar announcements.
Here is a list of (tentative) topics and speakers:
| Date | Topic | Speaker |
|---|---|---|
| 9/22 | Linear Regression | Xiaoxi Shen |
| 10/6 | Artificial Neural Network basics-Universal approximation | Doug Limmer |
| 10/20 | Grad Expo, no seminar meeting | |
| 11/3 | Artificial Neural Network basics-Gradient descent | Humu Mohammed and Usufu Nyakoojo |
| 11/17 | Difference between SGD and ADAM | Xiaoxi Shen and Jialong Li |
| 12/01 | Challenges: Impossibility of fairness | Hiro Lee Tanaka and Jake Fillman |
We will update this list with more info on the talk as we proceed. We are also compiling a list of suggested readings.
Suggested readings:
- Mike Nielsen. Neural networks and deep learning
- François Chollet. Deep Learning with Python
- Moritz Hardt and Benjamin Recht. PATTERNS, PREDICTIONS, AND ACTIONS: A story about machine learning.