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Big Data Mining


Course Code

EE226

Session

Spring 2019

Instructor(s)

Liyao XiangAssistant Professor (tenure-track)

John Hopcroft Center for Computer Science

Shanghai Jiao Tong University

Description

Course Overview

1. Introduction to Data Mining 
2. Fundamentals of Data Mining 
3. Basic Data Mining Alg. 
4. Supervised Learning 1 (Quiz 1) 
5. Supervised Learning 2 (Release course work) 
6. Supervised Learning 3 
7. Unsupervised Learning (Quiz 2) 
8. Graphical Prob. Models 1 (Course work due; Release Assignment) 
9. Graphical Prob. Models 2 (Assignment due) 
10. Knowledge Graphs (ACEMAP Introduction by Xu) + In-class test 
11. Learning to Rank 
12. Reinforcement Learning 
13. Adversarial Attacks 
14. Privacy-Preserving Data Mining 
15. Course Review (Quiz 3) 
16. Poster Session (Define a data mining problem -> Stating the difference from previous works -> Choosing a model to solve it -> Implementation -> Experimental results -> Report -> Poster) 

© John Hopcroft Center for Computer Science, Shanghai Jiao Tong University
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