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
9 Apr 17 Dependency Discovery:

Event-Event, Event Sequence-TS (time series), TS-TS

Neural Networks

Feature Selection


Dynamic Time Warping

10 Apr 24
11 May 6 (Saturday)

Fast Mitigation & Root Cause Analysis


Learning From Text

12 May 8

Event Prediction


Multi-Instance Learning

Transfer Learning

13 May 15
14 May 22 Observational Study  QED Methods
15 May 29 No Class due to Holidays
16 June 5 Project Presentation

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