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10th INTERNATIONAL GRAN CANARIA SCHOOL ON DEEP LEARNING

DeepLearn 2023 Summer

Las Palmas de Gran Canaria, Spain

July 17-21, 2023

https://irdta.eu/deeplearn/2023su/

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Co-organized by:

University of Las Palmas de Gran Canaria

Institute for Research Development, Training and Advice – IRDTA
Brussels/London

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Early registration: January 21, 2023

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FRAMEWORK:

DeepLearn 2023 Summer is part of a multi-event called Deep&Big 2023 consisting 
also of BigDat 2023 Summer. DeepLearn 2023 Summer participants will have the 
opportunity to attend lectures in the program of BigDat 2023 Summer as well if 
they are interested.

SCOPE:

DeepLearn 2023 Summer will be a research training event with a global scope 
aiming at updating participants on the most recent advances in the critical and 
fast developing area of deep learning. Previous events were held in Bilbao, 
Genova, Warsaw, Las Palmas de Gran Canaria, Guimarães, Las Palmas de Gran 
Canaria, Luleå, Bournemouth and Bari.

Deep learning is a branch of artificial intelligence covering a spectrum of 
current frontier research and industrial innovation that provides more 
efficient algorithms to deal with large-scale data in a huge variety of 
environments: computer vision, neurosciences, speech recognition, language 
processing, human-computer interaction, drug discovery, health informatics, 
medical image analysis, recommender systems, advertising, fraud detection, 
robotics, games, finance, biotechnology, physics experiments, biometrics, 
communications, climate sciences, geographic information systems, signal 
processing, genomics, etc. etc. Renowned academics and industry pioneers will 
lecture and share their views with the audience.

Most deep learning subareas will be displayed, and main challenges identified 
through 16 four-hour and a half courses and 2 keynote lectures, which will 
tackle the most active and promising topics. The organizers are convinced that 
outstanding speakers will attract the brightest and most motivated students. 
Face to face interaction and networking will be main ingredients of the event. 
It will be also possible to fully participate in vivo remotely.

An open session will give participants the opportunity to present their own 
work in progress in 5 minutes. Moreover, there will be two special sessions 
with industrial and employment profiles.

ADDRESSED TO:

Graduate students, postgraduate students and industry practitioners will be 
typical profiles of participants. However, there are no formal pre-requisites 
for attendance in terms of academic degrees, so people less or more advanced in 
their career will be welcome as well. Since there will be a variety of levels, 
specific knowledge background may be assumed for some of the courses. Overall, 
DeepLearn 2023 Summer is addressed to students, researchers and practitioners 
who want to keep themselves updated about recent developments and future 
trends. All will surely find it fruitful to listen to and discuss with major 
researchers, industry leaders and innovators.

VENUE:

DeepLearn 2023 Summer will take place in Las Palmas de Gran Canaria, on the 
Atlantic Ocean, with a mild climate throughout the year, sandy beaches and a 
renowned carnival. The venue will be:

Institución Ferial de Canarias
Avenida de la Feria, 1
35012 Las Palmas de Gran Canaria

https://www.infecar.es/

STRUCTURE:

2 courses will run in parallel during the whole event. Participants will be 
able to freely choose the courses they wish to attend as well as to move from 
one to another.

Also, if interested, participants will be able to attend courses developed in 
BigDat 2023 Summer, which will be held in parallel and at the same venue.

Full live online participation will be possible. The organizers highlight, 
however, the importance of face to face interaction and networking in this kind 
of research training event.

KEYNOTE SPEAKERS: (to be completed)

Aidong Zhang (University of Virginia), Concept-Based Models for Robust and 
Interpretable Deep Learning

PROFESSORS AND COURSES: (to be completed)

Eneko Agirre (University of the Basque Country), [introductory/intermediate] 
Natural Language Processing in the Large Language Model Era

Tae-Kyun Kim (Korea Advanced Institute of Science and Technology), 
[intermediate/advanced] Deep 3D Pose Estimation

Marcus Liwicki (Luleå University of Technology), [intermediate/advanced] 
Methods for Learning with Few Data

Ivan Oseledets (Skolkovo Institute of Science and Technology), [tba] Tensor 
Methods for Approximation of High-Dimensional Arrays and Their Applications in 
Machine Learning

Carlo Sansone (University of Naples Federico II), tba

Ponnuthurai N. Suganthan (Nanyang Technological University), 
[introductory/intermediate] Randomization-Based Deep and Shallow Learning 
Algorithms and Architectures

Savannah Thais (Columbia University), [intermediate] Applications of Graph 
Neural Networks: Physical and Societal Systems

Z. Jane Wang (University of British Columbia), [introductory/intermediate] 
Adversarial Deep Learning in Digital Image Security & Forensics

Li Xiong (Emory University), [introductory] Deep Learning and Privacy Enhancing 
Technology

Lihi Zelnik-Manor (Technion - Israel Institute of Technology), [introductory] 
Introduction to Computer Vision and the Ethical Questions It Raises

OPEN SESSION:

An open session will collect 5-minute voluntary presentations of work in 
progress by participants. They should submit a half-page abstract containing 
the title, authors, and summary of the research to da...@irdta.eu by July 9, 
2023.

INDUSTRIAL SESSION:

A session will be devoted to 10-minute demonstrations of practical applications 
of deep learning in industry. Companies interested in contributing are welcome 
to submit a 1-page abstract containing the program of the demonstration and the 
logistics needed. People in charge of the demonstration must register for the 
event. Expressions of interest have to be submitted to da...@irdta.eu by July 
9, 2023.

EMPLOYER SESSION:

Organizations searching for personnel well skilled in deep learning will have a 
space reserved for one-to-one contacts. It is recommended to produce a 1-page 
.pdf leaflet with a brief description of the organization and the profiles 
looked for to be circulated among the participants prior to the event. People 
in charge of the search must register for the event. Expressions of interest 
have to be submitted to da...@irdta.eu by July 9, 2023.

ORGANIZING COMMITTEE:

Carlos Martín-Vide (Tarragona, program chair)
Sara Morales (Brussels)
David Silva (London, organization chair)

REGISTRATION:

It has to be done at

https://irdta.eu/deeplearn/2023su/registration/

The selection of 8 courses requested in the registration template is only 
tentative and non-binding. For logistical reasons, it will be helpful to have 
an estimation of the respective demand for each course. During the event, 
participants will be free to attend the courses they wish as well as eventually 
courses in BigDat 2023 Summer.

Since the capacity of the venue is limited, registration requests will be 
processed on a first come first served basis. The registration period will be 
closed and the on-line registration tool disabled when the capacity of the 
venue will have got exhausted. It is highly recommended to register prior to 
the event.

FEES:

Fees comprise access to all courses and lunches. There are several early 
registration deadlines. Fees depend on the registration deadline.

The fees for on site and for online participation are the same.

ACCOMMODATION:

Accommodation suggestions will be available in due time at

https://irdta.eu/deeplearn/2023su/accommodation/

CERTIFICATE:

A certificate of successful participation in the event will be delivered 
indicating the number of hours of lectures.

Participants will be recognized 2 ECTS credits by University of Las Palmas de 
Gran Canaria.

QUESTIONS AND FURTHER INFORMATION:

da...@irdta.eu

ACKNOWLEDGMENTS:

Cabildo de Gran Canaria

Universidad de Las Palmas de Gran Canaria - Fundación Parque Científico 
Tecnológico

Universitat Rovira i Virgili

Institute for Research Development, Training and Advice – IRDTA, Brussels/London
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