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: May 19, 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 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 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] Generative Modeling 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.
 
INDUSTRIAL SESSION:
 
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) yahoo.com by July 2, 2017.
 
EMPLOYERS SESSION:
 
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) yahoo.com by July 2, 2017.
 
ORGANIZING COMMITTEE:
 
Pablo García Bringas (co-chair)
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 indicating the number of hours of lectures.
 
QUESTIONS AND FURTHER INFORMATION:
 
david.silva409 (at) yahoo.com
 
ACKNOWLEDGMENTS:
 
Universidad de Deusto
Universitat Rovira i Virgili