INTERNATIONAL SUMMER SCHOOL ON DEEP LEARNING

DeepLearn 2017 : early registration March 24

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INTERNATIONAL SUMMER SCHOOL ON DEEP LEARNING
DeepLearn 2017
Bilbao, Spain
July 17-21, 2017

Organized by :

University of Deusto

Rovira i Virgili University

http://grammars.grlmc.com/DeepLearn2017/
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--- Early registration deadline : March 24, 2017 ---
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SCOPE :

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 4 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.

ADDRESSED TO :

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.

REGIME :

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.

VENUE :

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 :

DeustoTech, School of Engineering
University of Deusto
Avda. Universidades, 24
48014 Bilbao, Spain

KEYNOTE SPEAKERS : (to be completed)

Richard Socher (Salesforce), Tackling the Limits of Deep Learning

PROFESSORS AND COURSES :

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
Behaviors

Rina Dechter (University of California, Irvine), [introductory]
Algorithms for Reasoning with Probabilistic Graphical Models

Li Deng (Microsoft Research), tba

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 Bioinformatics

Soo-Young Lee (Korea Advanced Institute of Science and Technology),
[intermediate/advanced] Multi-modal Deep Learning for the Recognition of
Human Emotions in the Real

Li Erran Li (Columbia University), [intermediate/advanced] Deep Learning
Security : Adversarial Examples and Adversarial Training

Michael C. Mozer (University of Colorado, Boulder),
[introductory/intermediate] Incorporating Domain Bias into Neural
Networks

Roderick Murray-Smith (University of Glasgow), [intermediate]
Applications of Deep Learning Models in Human-Computer Interaction
Research

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
Advances

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 Machines

Ying Nian Wu (University of California, Los Angeles),
[introductory/intermediate] Deep Generative Models and Unsupervised
Learning

Eric P. Xing (Carnegie Mellon University), [intermediate/advanced]
Statistical Machine Learning Perspectives of Extending Deep Neural
Networks : Kernels, Logics, Regularizers, Priors, and Distributed
Algorithms

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

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 title, authors, and summary of the research to david.silva409
(at) yahoo.com by July 9, 2017.

ORGANIZING COMMITTEE :

José Gaviria
Carlos Martín (co-chair)
Manuel Jesús Parra
Iker Pastor
Borja Sanz (co-chair)
David Silva

REGISTRATION :

It has to be done at

http://grammars.grlmc.com/DeepLearn2017/registration.php

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 :

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

ACCOMMODATION :

A suggestion for accommodation is available on the website.

CERTIFICATE :

Participants will be delivered a certificate of attendance including the
number of hours of lectures.

QUESTIONS AND FURTHER INFORMATION :

david.silva409 (at) yahoo.com

ACKNOWLEDGMENTS :

Universidad de Deusto

Universitat Rovira i Virgili