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If you are interested in joining a reading group this spring, please see below for a list of machine learning related groups. You’ll also find a list of ML-related courses being offered this semester (Spring 2020.) Be sure to keep them in mind as you schedule classes in future semesters.
Neither of these lists are complete lists, so feel free to seek out additional reading groups or classes that fit your interests and schedule.
ML Spring 2020 Reading Groups
*please contact the faculty member leading the group for more information
NLP and Social Interaction with Diyi Yang
Wednesday from 1:55-2:45pm
CCB 53
Reinforcement Learning Theory with Siva Theja Maguluri
Friday from 1-2:30pm
Groseclose 404
Differential Privacy with Rachel Cummings
Meeting date/time TBD
Statistical Learning Theory with Yao Xie
We plan to cover basic theoretical foundation from reading slides lectures and papers to start research in this area
Time TBD
ISyE, Room TBD
Law and Ethics of Machine Learning with Deven Desai
Location and time to be announced soon
Wednesday’s from 2-3 p.m.
Coda C1215 Midtown
NLP Reading Group
Every other Friday beginning 2/14 from 12-1 p.m. in Coda C1315 Grant Park
The group will meet for one hour each week, 12-1 PM on every other Friday, starting Feb 14 (pizza provided!). We will discuss recent papers in NLP research that have been published in top conferences such as ACL, EMNLP, and AAAI, and the papers will cover a variety of topics including contextual language models, model interpretability, bias detection, and text generation. The discussion will be led by one student volunteer who will present a short overview of the paper and provide engaging questions for group discussion. All participants are expected to read the paper prior to the meeting.
All those interested should (1) look at the list of paper suggestions here and (2) send an email to Ian (istewart6@gatech.edu) or Jiaao (jiaaochen@gatech.edu) to be added to the mailing list for the reading group.
Jacob Abernethy and Xiaoming Huo also plan on hosting reading groups this semester. Please contact them if you are interested in participating.
ML Spring 2020 Courses
ECE 4271
Instructor: Ghassan AlRegib
ISYE 6662 – Discrete Optimization
Instructor: Alejandro Toriello
CS 4650/7650 Natural Language Processing
Instructor: Diyi Yang
CS 4476/6476 – Computer Vision
Instructor: Judy Hoffman
CS 4496/7497 - Computer Animation
Instructor: Sehoon Ha
*covers a bit of reinforcement learning
ISYE 6402 – Time Series Analysis
Instructor: Xiaoming Huo
ISYE 6783 – Financial Data Analysis
Instructor: Xiaoming Huo
ECE 8803 – Probabilistic Graphical Models
Instructor: Faramarz Fekri
PUBP 8751
Instructor: Omar I. Asensio
ECON 8803 – Big Data and Policy
Instructor: Omar I. Asensio
CS 3510 – Algorithms
Instructor: Constatine Dovrolis
BMED 6517 – Machine Learning in Biosciences
Instructor: Peng Qiu
CSE 6240: Web Search and Text Mining
Instructor: Srijan Kumar
It discusses several important machine learning topics including text mining, network science, and social media analytics.
CS6550: Continuous Algorithms: Optimization and Sampling
Instructor: Santosh Vempala
AE 8803: Optimal Transport Theory and Applications
Instructor: Yongxin Chen