Machine Learning Journal Club

The Machine Learning Journal Club will meet every other Thursday to present and discuss two research papers from the recent machine learning literature. Participating graduate students will give the presentations, which are quite informal (15-20 min). The main idea is to quickly get to the contributions of each paper and discuss its significance. The general theme is around the following.

- New, interesting and impactful papers in machine learning.
- Papers that are general enough to be useful to any ML researcher rather than a very specific application.
- Seminal papers that may be old (papers that pioneered a sub field in ML).
- Informational sessions that are useful to our grad students in the trenches (example topics: troubleshooting    neural nets, training big neural nets faster, techniques to handle huge datasets and optimize ML pipelines).

We invite faculty members and graduate students with an interest in the fast-moving fields of machine learning and artificial intelligence to join the club meetings and make the discussions vibrant and interesting.

Meeting schedule:

Every other Thursday, 12:30 - 1:30 pm, throughout the academic year, please check the presentation schedule below for the room location. 



Sunanda Gamage (

If you would like to be added to the Machine Learning Club Mailing List, please email Sunanda directly. 

Participating faculty members:

Jagath Samarabandu, Abdallah Shami, Katarina Grolinger, Serguei Primak, Xianbin Wang


Presentation Schedule: 

Date, Time Location Presenter Paper
Thursday, November 28th, 12:30-1:30pm SEB 2100 Sunanda Gamage

"Methods for interpreting and understanding deep neural networks”, G. Montavon, W. Samek, and K.-R. Müller, Feb. 2018.

Cesar Gomez

Human-level control through deep reinforcement learning”, V. Mnih et al., Feb. 2015

Thursday, January 16, 2020 12:30-1:30pm SEB 2100  Serguei Primak

When Machine Learning Meets Wireless Cellular Networks: Deployment, Challenges, and Applications”, U. Challita, H. A. Ryden, and H. Tullberg, Nov. 2019.

Thursday January 30, 2020 12:30-1:30pm SEB 2100 Norman Tasfi

Learning to reinforcement learn”, J. X. Wang, Z. Kurth-Nelson et al, Nov. 2016.

Thursday, February 13, 2020 SEB 2100 Javad Khodabakhsh

Presentation Title: "Machine learning applications in power systems"