|
|
Boost Interest : |
From: IRDTA (irdta_at_[hidden])
Date: 2021-02-17 21:03:14
*To be removed from our mailing list, please respond to
this message with UNSUBSCRIBE in the subject line*
******************************************************************
4th INTERNATIONAL SCHOOL ON DEEP LEARNING
DeepLearn 2021 Summer
Las Palmas de Gran Canaria, Spain
July 26-30, 2021
Co-organized by:
Department of Information Engineering
Marche Polytechnic University
Institute for Research Development, Training and Advice – IRDTA
Brussels/London
https://irdta.eu/deeplearn2021s/
******************************************************************
--- Early registration deadline: February 24, 2021 ---
************************************************
SCOPE:
DeepLearn 2021 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 and Warsaw.
Deep learning is a branch of artificial intelligence covering a
spectrum of current exciting research and industrial innovation
that provides more efficient algorithms to deal with large-scale
data in neurosciences, computer vision, speech recognition,
language processing, human-computer interaction, drug discovery,
biomedical informatics, healthcare, recommender systems, learning
theory, robotics, games, 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 24 four-hour and a half courses and
3 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.
Interaction will be a main component of the event.
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 recruitment profiles.
ADDRESSED TO:
Master's students, PhD students, postdocs, and industry
practitioners will be typical profiles of participants. However,
there are no formal pre-requisites for attendance in terms of
academic degrees. Since there will be a variety of levels,
specific knowledge background may be assumed for some of the
courses. Overall, DeepLearn 2021 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 and discuss with major researchers,
industry leaders and innovators.
VENUE:
DeepLearn 2021 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:
Palacio de Congresos Gran Canaria
Institución Ferial de Canarias
Avenida de la Feria, 1
35012 Las Palmas de Gran Canaria
https://www.infecar.es/index.php?option=com_k2&view=item&layout=item&id=360&Itemid=896
STRUCTURE:
3 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.
KEYNOTE SPEAKERS:
Nello Cristianini (University of Bristol), Data, Intelligence and
Shortcuts
Petia Radeva (University of Barcelona), Uncertainty Modeling and
Deep Learning in Food Analysis
Indrė Žliobaitė (University of Helsinki), Any Hope for Deep
Learning in Deep Time?
PROFESSORS AND COURSES: (to be completed)
Ignacio Arganda-Carreras (University of the Basque Country),
[introductory/intermediate] Deep Learning for Bioimage Analysis
Rita Cucchiara (University of Modena and Reggio Emilia),
[intermediate/advanced] Learning to Understand Humans and Their
Behaviour
Thomas G. Dietterich (Oregon State University), [introductory]
Machine Learning Methods for Robust Artificial Intelligence
Georgios Giannakis (University of Minnesota), [advanced]
Ensembles for Online, Interactive and Deep Learning Machines with
Scalability, and Adaptivity
Sergei V. Gleyzer (University of Alabama),
[introductory/intermediate] Machine Learning Fundamentals and
Their Applications to Very Large Scientific Data: Rare Signal and
Feature Extraction, End-to-end Deep Learning, Uncertainty
Estimation and Realtime Machine Learning Applications in Software
and Hardware
Çağlar Gülçehre (DeepMind), [intermediate/advanced] Deep
Reinforcement Learning
Balázs Kégl (Huawei Technologies), [introductory] Deep
Model-based Reinforcement Learning
Vincent Lepetit (ENPC ParisTech), [intermediate] Deep Learning
and 3D Geometry
Geert Leus (Delft University of Technology),
[introductory/intermediate] Graph Signal Processing: Introduction
and Connections to Distributed Optimization and Deep Learning
Andy Liaw (Merck Research Labs), [introductory] Machine Learning
and Statistics: Better together
Abdelrahman Mohamed (Facebook AI Research),
[introductory/advanced] Recent Advances in Automatic Speech
Recognition
Hermann Ney (RWTH Aachen University), [intermediate/advanced]
Speech Recognition and Machine Translation: From Statistical
Decision Theory to Machine Learning and Deep Neural Networks
Lyle John Palmer (University of Adelaide),
[introductory/advanced] Epidemiology for Machine Learning
Investigators
Jan Peters (Technical University of Darmstadt), [intermediate]
Robot Learning
José C. PrÃncipe (University of Florida), [intermediate/advanced]
Cognitive Architectures for Object Recognition in Video
Björn W. Schuller (Imperial College London),
[introductory/intermediate] Deep Signal Processing
Sargur N. Srihari (University at Buffalo), [introductory]
Generative Models in Deep Learning
Johan Suykens (KU Leuven), [introductory/intermediate] Deep
Learning, Neural Networks and Kernel Machines
Gaël Varoquaux (INRIA), [intermediate] Representation Learning in
Limited Data Settings
René Vidal (Johns Hopkins University), [intermediate/advanced]
Mathematics of Deep Learning
Haixun Wang (Instacart), [introductory/intermediate]
Abstractions, Concepts, and Machine Learning
Ming-Hsuan Yang (University of California, Merced),
[intermediate/advanced] Learning to Track Objects
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 david_at_irdta.eu by July 18, 2021.
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 participating in the demonstration must
register for the event. Expressions of interest have to be
submitted to david_at_irdta.eu by July 18, 2021.
EMPLOYER SESSION:
Firms 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
company 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 david_at_irdta.eu by July 18, 2021.
ORGANIZING COMMITTEE:
Emanuele Frontoni (Ancona, co-chair)
Carlos MartÃn-Vide (Tarragona, program chair)
Sara Moccia (Ancona)
Sara Morales (Brussels)
Marina Paolanti (Ancona)
Manuel J. Parra-Royón (Granada)
Luca Romeo (Ancona)
David Silva (London, co-chair)
REGISTRATION:
It has to be done at
https://irdta.eu/deeplearn2021s/registration/
The selection of up to 8 courses requested in the registration
template is only tentative and non-binding. For the sake of
organization, 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.
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 get 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.
ACCOMMODATION:
Suggestions for accommodation will be available in due time at
https://irdta.eu/deeplearn2021s/accommodation/
CERTIFICATE:
A certificate of successful participation in the event will be
delivered indicating the number of hours of lectures.
QUESTIONS AND FURTHER INFORMATION:
david_at_irdta.eu
ACKNOWLEDGMENTS:
Dipartimento di Ingegneria dell'Informazione, UniversitÃ
Politecnica delle Marche
Institute for Research Development, Training and Advice – IRDTA,
Brussels/London
Institución Ferial de Canarias