https://github.com/zhenye-na/analysis-of-network-data
IE532: Analysis of Network Data in 2017 Fall, UIUC
https://github.com/zhenye-na/analysis-of-network-data
convolutional-neural-networks deep-learning graph-convolutional-network minimum-spanning-trees network-analysis shortest-path-algorithm
Last synced: 8 months ago
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IE532: Analysis of Network Data in 2017 Fall, UIUC
- Host: GitHub
- URL: https://github.com/zhenye-na/analysis-of-network-data
- Owner: Zhenye-Na
- Created: 2018-01-22T01:21:34.000Z (almost 8 years ago)
- Default Branch: master
- Last Pushed: 2018-01-22T01:30:00.000Z (almost 8 years ago)
- Last Synced: 2025-01-11T15:47:38.405Z (10 months ago)
- Topics: convolutional-neural-networks, deep-learning, graph-convolutional-network, minimum-spanning-trees, network-analysis, shortest-path-algorithm
- Language: Jupyter Notebook
- Homepage: https://ise.illinois.edu/courses/profile/IE532
- Size: 5.46 MB
- Stars: 1
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# IE532: Analysis of Network Data in 2017 Fall, UIUC.
This course will focus on statistical aspects analyzing network data. It will review illustrative problems relating to aggregation of information, decision-making, and inference tasks over various graphical models and networks.
**Topics**
- Cycles and Trees
- Network Flow
- Matching Problems
- Spectral Methods
- Linear Programming
- Online Algorithms
## Course Information:
4 graduate hours. No professional credit.
## Prerequisite:
MATH 412. ISE graduate students and students enrolled in the Master of Science in Advanced Analytics (MCAA) are eligible to take the course.
## Instructor:
[Oh, Sewoong (Primary)](https://ise.illinois.edu/directory/profile/swoh)