Title: Machine Learning Techniques and Selected Applications for Big Data

Lecturer: Stan Matwin (Dalhousie University, Canada)

Period: February 22, 25, 29 - March 3, 7, 10, 14, 17, 21, 24 2016

Timetable: Mon. 11:00-13:00  Thu. 14:00-16:00

Place: Department of Computer Science Sala “seminari ovest"

Stan Matwin is a Professor and Canada Research Chair in the Faculty of Computer Science at Dalhousie University, Canada,  where he directs the Institute for Big Data Analytics. He is also a Professor at the Institute of Computer Science, Polish Academy of Sciences. His research interests are in text analytics, data mining, as well as in data privacy. Author and co-author of more than 250 research papers and articles, Stan is a former President of the Canadian Artificial Intelligence Society, a member of the Scientific Council of the Polish Artificial Intelligence Society, and a member of Association Francaise pour l’Intelligence Artificielle.


1. Intro (def, challenges, nosql etc.)  2h

2. Linear methods 2h

3. Bayesian Methods 3h

4. Stream Data Processing: VFDTs 2h

5. Vizualization: basics, examples 3h

6. Privacy for Big Data: data summaries (scripts, Bloom filters), ABAC approaches (Acumulo) 3h

7. Applications: Oceans 2h

8. Applications: Big Data in the Public Sector 2h

9. Data tagging challenges for Big Data: crowdsourcing, reCaptcha 1h