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