International Summer School on Deep Learning Call for Participation

DeepLearn 2017
Bilbao, Spain
July 17-21, 2017
Organized by:
University of Deusto
Rovira i Virgili University
--- Regular registration deadline: July 14, 2017 ---
DeepLearn 2017 will be a research training event with a global scope
aiming at updating participants about the most recent advances in the
critical and fast developing area of deep learning. This is a branch
of artificial intelligence covering a spectrum of current exciting
machine learning research and industrial innovation that provides more
efficient algorithms to deal with large-scale data in neuroscience,
computer vision, speech recognition, language processing, drug
discovery, biomedical informatics, 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 2 keynote lectures, 30 six-hour courses, and 1
round table, 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.
In principle, graduate students, doctoral students and postdocs 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. DeepLearn 2017 is also appropriate
for more senior academics and practitioners who want to keep
themselves updated on recent developments and future trends. All will
surely find it fruitful to listen and discuss with major researchers,
industry leaders and innovators.
In addition to keynotes, 3-4 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.
DeepLearn 2017 will take place in Bilbao, the largest city in the
Basque Country, famous for its gastronomy and the seat of the
Guggenheim Museum. The venue will be:
Palacio Euskalduna
Avda. Abandoibarra, 4
48011 Bilbao, Spain
Li Deng (Citadel), Recent Advances in Unsupervised Deep Learning
Richard Socher (Salesforce), Tackling the Limits of Deep Learning
Narendra Ahuja (University of Illinois, Urbana-Champaign),
[introductory/intermediate] Basics of Deep Learning with Applications
to Image Processing, Pattern Recognition and Computer Vision
Pierre Baldi (University of California, Irvine),
[intermediate/advanced] Deep Learning: Theory and Applications to the
Natural Sciences
Sven Behnke (University of Bonn), [intermediate] Visual Perception
using Deep Convolutional Neural Networks
Mohammed Bennamoun (University of Western Australia),
[introductory/intermediate] Deep Learning for Computer Vision
Hervé Bourlard (Idiap Research Institute), [intermediate/advanced]
Deep Sequence Modeling: Historical Perspective and Current Trends
Thomas Breuel (NVIDIA Corporation), [intermediate] Segmentation,
Processing, and Tracking, with Applications to Video, Gaming, VR, and
Self-driving Cars
George Cybenko (Dartmouth College), [intermediate] Deep Learning of
Rina Dechter & Alexander Ihler (University of California, Irvine),
[introductory] Algorithms for Reasoning with Probabilistic Graphical
Li Deng (Citadel), [introductory/advanced] An Overview of Deep
Learning for Speech, Image, Text, and Multi-modal Processing
Jianfeng Gao (Microsoft Research), [introductory/intermediate] An
Introduction to Deep Learning for Natural Language Processing
Michael Gschwind (IBM T.J. Watson Research Center),
[introductory/intermediate] Deploying Deep Learning Applications at
the Enterprise Scale
Yufei Huang (University of Texas, San Antonio),
[intermediate/advanced] Deep Learning for Precision Medicine and
Biomedical informatics
Soo-Young Lee (Korea Advanced Institute of Science and Technology),
[intermediate/advanced] Multi-modal Deep Learning for the Recognition
of Human Emotions in the Wild
Li Erran Li (Columbia University), [intermediate/advanced] Deep
Reinforcement Learning: Recent Advances and Frontiers
Michael C. Mozer (University of Colorado, Boulder),
[introductory/intermediate] Incorporating Domain Bias into Neural
Roderick Murray-Smith (University of Glasgow), [intermediate]
Applications of Deep Learning Models in Human-Computer Interaction
Hermann Ney (RWTH Aachen University), [intermediate/advanced] Speech
Recognition and Machine Translation: From Statistical Decision Theory
to Machine Learning and Deep Neural Networks
Jose C. Principe (University of Florida), [intermediate/advanced]
Cognitive Architectures for Object Recognition in Video
Marc'Aurelio Ranzato (Facebook AI Research),
[introductory/intermediate] Learning Representations for Vision,
Speech and Text Processing Applications
Maximilian Riesenhuber (Georgetown University),
[introductory/intermediate] Deep Learning in the Brain
Ruslan Salakhutdinov (Carnegie Mellon University),
[intermediate/advanced] Foundations of Deep Learning and its Recent
Alessandro Sperduti (University of Padua), [intermediate/advanced]
Deep Learning for Sequences
Jimeng Sun (Georgia Institute of Technology), [introductory]
Interpretable Deep Learning Models for Healthcare Applications
Julian Togelius (New York University), [intermediate] (Deep) Learning
for (Video) Games
Joos Vandewalle (KU Leuven), [introductory/intermediate] Data
Processing Methods, and Applications of Least Squares Support Vector
Ying Nian Wu (University of California, Los Angeles),
[introductory/intermediate] Generative Modeling and Unsupervised
Eric P. Xing (Carnegie Mellon University), [intermediate/advanced]
Statistical Machine Learning Perspectives of Extending Deep Neural
Networks: Kernels, Logics, Regularizers, Priors, and Distributed
Georgios N. Yannakakis (University of Malta),
[introductory/intermediate] Deep Learning for Games - But Not for
Playing them
Scott Wen-tau Yih (Microsoft Research), [introductory/intermediate]
Continuous Representations for Natural Language Understanding
Richard Zemel (University of Toronto), [introductory/intermediate]
Learning to Understand Images and Text
An open session will collect 5-minute voluntary presentations of work
in progress by participants. They should submit a half-page abstract
containing title, authors, and summary of the research to
david.silva409 (at) by July 9, 2017.
A specific session will be devoted to demonstrations of practical uses
of deep learning in industrial processes. Companies/people interested
in contributing are welcome to submit a 1-page abstract containing the
program of the demonstration, the duration requested and the logistics
necessary. At least one of the people participating in the
demonstration should have registered for the event. Expressions of
interest have to be submitted to david.silva409 (at) by July
2, 2017.
Firms searching for personnel well skilled in deep learning will have
a space reserved for one-to-one contacts. At least one of the people
in charge of the search should have registered for the
event. Expressions of interest have to be submitted to david.silva409
(at) by July 2, 2017.
Pablo García Bringas (co-chair)
José Gaviria
Carlos Martín (co-chair)
Manuel Jesús Parra
Iker Pastor
Borja Sanz (co-chair)
David Silva
It has to be done at
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 approximation of the
respective demand for each course.
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 facility disabled
when the capacity of the venue will be complete. It is much
recommended to register prior to the event.
Fees comprise access to all courses and lunches. There are several
early registration deadlines. Fees depend on the registration
Suggestions for accommodation are available on the website.
Participants will be delivered a certificate of attendance indicating
the number of hours of lectures.
david.silva409 (at)
Universidad de Deusto
Universitat Rovira i Virgili