The technical focus of this summer school is on fundamentals
and algorithmic advances for learning from large volumes of
data, with emphasis on network (i.e., graph) data. Topics
covered go all the way from learning graph representations of
complex signals, to tensor decompositions of multi-aspect data
and learning efficient signal representations via state-of-the-art
deep learning architectures. To better illustrate the concepts
taught, a gamut of diverse applications will be considered,
including communication, social, brain, and power networks,
Internet of Things technologies, and artificial intelligence.
Fundamentals• Statistical analysis of network data
• Tensor methods for signal processing and machine learning
• Distributed optimization for large-scale analytics
• Graph signal processing
• Inference of graph topologies and network processes
• Representation learning and deep reinforcement learning
• Graph convolutional neural networks
Applications• Social networks
• Internet of things
• Brain networks and neuroimaging
• Artificial intelligence
• Smart grid analytics
• Resource allocation for 5G networks
Registration fees (in US dollars)
Registration includes all lectures, materials and lecture notes,
lunches and coffee breaks for all five days, and a social dinner.
Student IEEE-SPS or EURASIP member $ 400
Student IEEE Member $ 420
Student non-member $ 460
IEEE-SPS or EURASIP member $ 500
IEEE Member $ 520
Non-member $ 600
APPLICATION DEADLINE April 30, 2019
www.dtc.umn.edu/lecce2019school
IEEE-SPS / EURASIP Summer School
T
May 20-24, 2019 – Lecce, Italy
he 2019 IEEE-SPS / EURASIP Summer School on
“Network- and Data-driven Learning: Fundamentals
and Applications,” will take place in Lecce, Italy. It will
bring together researchers to share exciting advances
in network and data sciences theory and applications.
The event will host students interested in signal processing,
offering them opportunities to network with world-renowned
professors and industry researchers as well as to engage in
hands-on tutorials in signal processing and machine
learning. In addition to the beautiful ambiance offered by
“The Florence of the South of Italy,” attendants will benefit
from a stimulating environment to learn about the latest
advances in an exciting field. Students will have the
possibility to present their current research work in a poster
session.
General ChairsGeorgios B. Giannakis, University of Minnesota
Gonzalo Mateos, University of Rochester
Local Arrangements ChairsFrancesco Bandiera, University of Salento
Fulvio Gini, University of Pisa
LecturersSergio Barbarossa, University of Rome
Lieven De Lathauwer, KU Leuven
Georgios B. Giannakis, University of Minnesota
Geert Leus, TU Delft
Antonio G. Marques, King Juan Carlos University
Gonzalo Mateos, University of Rochester
Alejandro Ribeiro, University of Pennsylvania
Luca Sanguinetti, University of Pisa
Anna Scaglione, Arizona State University
Gesualdo Scutari, Purdue University
Pablo Sprechmann, Google DeepMind
Dimitri Van De Ville, EPFL
Network- and Data-driven Learning:
Fundamentals and Applications
Call for participation
Piazza Duomo, Lecce
Otranto