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2020 ECE TUC Virtual Summer School on Data Analysis
On August 5-7, 2020, the School of Electrical and Computer Engineering (ECE) of the Technical University of Crete (TUC) will host the virtual Summer School “2020 ECE TUC Summer School on Data Analysis.”
One former ECE TUC faculty member, four ECE TUC graduates, who are currently faculty members, and four ECE TUC graduates, who are currently PhD candidates, will present and discuss their recent research results on Data Analysis. An “Open Problems Session” will complement the presentations and discussions.
The main objectives of the summer school are to increase the visibility of ECE TUC, to create and strengthen ties between ECE TUC and top universities worldwide, and to cultivate a collegial culture among current and former ECE TUC members, worldwide.
The event will be open to all members of the TUC community (students, research associates, faculty members).
If you plan to attend, please fill out the registration form.
Location & Schedule
Information on "how to attend the event" is available on our Attending page.
Details on the schedule can be found on our Talks & Schedule page.
5 August
Panos Markopoulos
Rochester Institute of Technology
Improving CNNs Towards Real-Time Multi-modal Object Detection in Remote Sensing Imagery
Anastasios (Tasos) Kyrillidis
Rice University
Distributed learning of deep neural networks using independent subnet training
Evangelos (Vagelis) Papalexakis
University of California Riverside
Tensor Decompositions for Graph Mining, Gravitational Wave Detection, and Adversarial Machine Learning
6 August
Vassilis Digalakis Jr. (PhD Student)
MIT’s Operations Research Center
The Backbone Method for Ultra-High Dimensional Sparse Machine Learning
Dimitrios Chachlakis (PhD Student)
Rochester Institute of Technology
The Lp-PC of a Matrix, for p<1
Yorgos Tsitsikas (PhD Student)
University of California, Riverside
Discovering the number of latent components in tensor decomposition
7 August
Paris Karakasis (PhD Student)
University of Virginia
Multi-subject Task-related fMRI Data Analysis via Generalized Canonical Correlation Analysis
Nikos Sidiropoulos
University of Virginia
Canonical Identification: A Principled Alternative to Neural Networks
Dimitrios Papailiopoulos
University of Wisconsin-Madison
Learning is Pruning