3rd cHiPSet TRAINING SCHOOL
“Large-Scale Data Mining and Machine Learning
for Big Data Analytics”
Aristotle University of Thessaloniki, Thessaloniki, Greece
September 19 – 21, 2018
About
cHiPSet is promoting a Training School on “Large-Scale Data Mining and Machine Learning for Big Data Analytics”. It mainly targets PhD students, researchers and skilled practitioners. The training school within COST Action IC1406 will be positioned at the crossroads where Big Data meets Data Mining and Machine Learning, with a target towards applications of these areas in modern technology. The primary target of the School is to train participants in algorithmic and implementation aspects related to large-scale data analytics. Nowadays, there is a high research interest in the areas of Data Mining and Machine Learning, towards designing scalable algorithms for efficient Knowledge Discovery from datasets that are characterized by one or more of the well-known V’s (e.g., volume, velocity, variety, veracity, value).
The training school within COST Action IC1406 features presentations with detailed descriptions of the selected data and applications, as well as hands on experience in leveraging modern distributed systems on real-world Big Data problems. At the end, participants will be able to understand in depth fundamental topics related to Knowledge Discovery at scale and apply these techniques to different types of problems. This training event is sponsored by COST Action IC1406 cHiPSet and organized by the School of Informatics of Aristotle University of Thessaloniki, Greece (http://www.csd.auth.gr/en/).
Main Topics and Trainers
- Let there be Spark! Data Mining and Machine Learning at Scale, Apostolos Papadopoulos, Aristotle University of Thessaloniki, Greece (http://datalab.csd.auth.gr/~apostol/)
- Analytics for Social Good: Addressing Social Biases in Algorithmic Systems, Jahna Otterbacher, Open University of Cyprus (http://www.jahna-otterbacher.net/)
- Algorithms in Data Science, Ioannis Emiris, University of Athens & Athena Research Center (http://cgi.di.uoa.gr/~emiris/index-eng.html)
- Cloud Performance – Resource Allocation and Scheduling Issues, Helen Karatza, Aristotle University of Thessaloniki (http://agent.csd.auth.gr/~karatza/)
- Beyond MapReduce: Stream-based Data Analytics, Horacio González-Vélez, National College of Ireland (https://www.linkedin.com/in/horaciogv/)
- Workflow Optimization for Big Data Analytics, Georgia Kougka, Aristotle University of Thessaloniki (https://www.linkedin.com/in/georgia-kougka-7a68193a/)
About the Venue
Thessaloniki is very well connected with major European cities and many airlines have regular daily flights (Aegean, Lufthansa, Austrian, Al Italia, SAS, Air Serbia, Ryanair, Transavia, EasyJet and many more). Also, Thessaloniki is connected via Athens International Airport, and there are many local flights from Athens to Thessaloniki daily. There is a large local bus network in the city. The Aristotle University Campus is located at a walking distance from the city center and bus stations and it is easily reachable. The school will take place in KEDEA Research Dissemination Center, 3is Septemvriou, 54636, Thessaloniki. Please check the following Google Maps link for the exact location.
Local Organizing Committee
- Yannis Manolopoulos, Professor, School of Informatics, Aristotle University of Thessaloniki, Greece
- Helen Karatza, Professor Emeritus, School of Informatics, Aristotle University of Thessaloniki, Greece
- Apostolos Papadopoulos, Associate Professor, School of Informatics, Aristotle University of Thessaloniki, Greece
School Leaflet (pdf file for downolading)
Presentations
- Algorithms in Data Science, Prof. Ioannis Emiris
- Workflow Optimisation for Big Data Analytics, Dr. Georgia Kougka
- Analytics for Social Good: Addressing Social Biases in Algorithmic Systems, Prof. Jahna Otterbacher
- Cloud Performance – Resource Allocation and Scheduling Issues, Prof. Helen Karatza
- Let there be Spark! Data Mining and Machine Learning at Scale, Prof. Apostolos Papadopoulos