Advanced Network Management-spring2017

In the project, a team of 2 or 3 students will use the real data to do the following tasks step by step:

a. Data processing and visualization

b. Kendall correlation and Information Gain

c. Decision Tree

d. Anomaly detection based on Time Series Prediction

e. Anomaly detection through machine learning

Week	Date	Topic, Papers, Slides and Reading List	Algorithms & Techniques
1	Feb 20	Course Introduction
2	Feb 27	Video streaming & Web	Data Visualization Correlation, Regression, Information gain, Decision trees, Regression trees
3	Mar 6
4	Mar 13
5	Mar 20
6	Mar 27	Anomaly detection for time series	Time series Algorithms. Random Forests
7	Apr 1 (Saturday)	Anomaly localization for time series	Association Mining Occam’s Razor
8	Apr 10	Anomaly localization for time series	Association Mining Occam’s Razor
9	Apr 17	Dependency Discovery: Event-Event, Event Sequence-TS (time series), TS-TS	Neural Networks Feature Selection Clustering Dynamic Time Warping
10	Apr 24
11	May 6 (Saturday)	Fast Mitigation & Root Cause Analysis	Regularization Learning From Text
12	May 8	Event Prediction	SVM Multi-Instance Learning Transfer Learning
13	May 15	Event Prediction	SVM Multi-Instance Learning Transfer Learning
14	May 22	Observational Study	QED Methods
15	May 29	No Class due to Holidays
16	June 5	Project Presentation