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DeepLearn 2018: regular registration July 20
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2nd INTERNATIONAL SUMMER SCHOOL ON DEEP
LEARNING
DeepLearn 2018
Genova, Italy
July 23-27, 2018
Organized by:
University of Genova
IRDTA – Brussels/London
http://grammars.grlmc.com/DeepLearn2018/
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--- Regular registration deadline: July 20, 2018 ---
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SCOPE:
DeepLearn 2018 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 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 2 keynote lectures, 24 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. 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 2018 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.
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.
VENUE:
DeepLearn 2018 will take place in Genova, the capital city of
Liguria, inscribed on the UNESCO World Heritage List and with one
of the most important ports of the Mediterranean. The venue will
be:
Porto Antico di Genova – Centro Congressi
Magazzini del Cotone – Module 10
16128 Genova, Italy
KEYNOTE SPEAKERS:
Paolo Frasconi (University of Florence), Bilevel Programming for
Hyperparameter Optimization and Meta-Learning
Marco Gori (University of Siena), Motion Supervision in Visual
Environments
PROFESSORS AND COURSES:
Tülay Adalı (University of Maryland, Baltimore County),
[introductory/intermediate] Data Fusion through Matrix and Tensor
Decompositions: Linear, Multilinear, and Nonlinear Models and
their Applications
Pierre Baldi (University of California, Irvine),
[intermediate/advanced] Deep Learning: Theory, Algorithms, and
Applications to the Natural Sciences
Thomas Breuel (NVIDIA Corporation), [intermediate] Design and
Implementation of Deep Learning Applications
Joachim M. Buhmann (Swiss Federal Institute of Technology Zurich),
[introductory/advanced] Model Selection by Algorithm Validation
Sergei V. Gleyzer (University of Florida),
[introductory/intermediate] Feature Extraction, End-end Deep
Learning and Applications to Very Large Scientific Data: Rare
Signal Extraction, Uncertainty Estimation and Realtime Machine
Learning Applications in Software and Hardware
Marco Gori (University of Siena), Constrained Learning and
Reasoning with Constraints
Michael Gschwind (IBM Global Chief Data Office),
[introductory/intermediate] Deploying Deep Learning at Enterprise
Scale
Namkug Kim (Asan Medical Center), [intermediate] Deep Learning for
Computer Aided Detection/Diagnosis in Radiology and Pathology
Sun-Yuan Kung (Princeton University), [introductory] A Methodical
and Cost-effective Approach to Optimization/Generalization of
Deep Learning Networks
Li Erran Li (Uber ATG), [intermediate/advanced] Deep Reinforcement
Learning: Foundations, Recent Advances and Frontiers
Dimitris N. Metaxas (Rutgers University), [advanced] Adversarial,
Discriminative, Recurrent, and Scalable Deep Learning Methods for
Human Motion Analytics, Medical Image Analysis, Scene
Understanding and Image Generation
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), [introductory/advanced]
Cognitive Architectures for Object Recognition in Video
Douglas A. Reynolds (Massachusetts Institute of Technology) &
Najim Dehak (Johns Hopkins University),
[introductory/intermediate] More than Words Can Say: Machine and
Deep Learning for Speaker, Language, and Emotion Recognition from
Speech
Björn Schuller (Imperial College London), [intermediate/advanced]
Deep Learning for Signal Analysis
Michèle Sebag (French National Center for Scientific Research,
Gif-sur-Yvette), [intermediate] Representation Learning, Domain
Adaptation and Generative Models with Deep Learning
Ponnuthurai N Suganthan (Nanyang Technological University),
[introductory/intermediate] Learning Algorithms for
Classification, Forecasting and Visual Tracking
Johan Suykens (KU Leuven), [introductory/intermediate] Deep
Learning and Kernel Machines
Kenji Suzuki (Tokyo Institute of Technology),
[introductory/advanced] Deep Learning in Medical Image Processing,
Analysis and Diagnosis
René Vidal (Johns Hopkins University), [intermediate/advanced]
Mathematics of Deep Learning
Eric P. Xing (Carnegie Mellon University), [intermediate/advanced]
A Statistical Machine Learning Perspective of Deep Learning:
Algorithm, Theory, Scalable Computing
Ming-Hsuan Yang (University of California, Merced),
[intermediate/advanced] Learning to Track Objects
Mohammed J. Zaki (Rensselaer Polytechnic Institute),
[introductory] Introductory Tutorial on Regression and Deep
Learning
Yudong Zhang (University of Leicester),
[introductory/intermediate] Convolutional Neural Network and Its
Variants
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@irdta.eu by July 15, 2018.
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. At
least one of the people participating in the demonstration must
register for the event. Expressions of interest have to be
submitted to
david@irdta.eu by July 15, 2018.
EMPLOYERS 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. At least one of the people in
charge of the search must register for the event. Expressions of
interest have to be submitted to
david@irdta.eu by July 15, 2018.
ORGANIZING COMMITTEE:
Alberto Cabri (Genova)
Francesco Masulli (Genova, co-chair)
Sara Morales (Brussels)
Manuel J. Parra-Royón (Granada)
Stefano Rovetta (Genova)
David Silva (London, co-chair)
REGISTRATION:
It has to be done at
http://grammars.grlmc.com/DeepLearn2018/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 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
facility disabled when the capacity of the venue is 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 can be found at
http://www.deeplearn-hotels.promoest.com/hp.aspx?s=0
CERTIFICATE:
A certificate of successful participation in the event will be
delivered indicating the number of hours of lectures.
QUESTIONS AND FURTHER INFORMATION:
david@irdta.eu
ACKNOWLEDGMENTS:
Università degli studi di Genova
Institute for Research Development, Training and Advice (IRDTA) –
Brussels/London