[loginf] DeepLearn 2020: early registration March 26
irdta at irdta.eu
Thu Mar 12 07:08:04 CET 2020
DeepLearn 2020: early registration March 26*To be removed from our mailing list, please respond to this message with UNSUBSCRIBE in the subject line*
4th INTERNATIONAL SUMMER SCHOOL ON DEEP LEARNING
León, Guanajuato, Mexico
July 27-31, 2020
Center for Research in Mathematics, A.C. (CIMAT-CONACyT)
Institute for Research Development, Training and Advice (IRDTA)
--- Early registration deadline: March 26, 2020 ---
DeepLearn 2020 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 20 four-hour and a half courses, 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.
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 2020 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.
DeepLearn 2020 will take place in León, the most populous city in the state of Guanajuato, in central Mexico, and a major economic pole in the country with specialization in leather industry. The venue will be:
Blvd. Adolfo López Mateos esq. Blvd. Francisco Villa
Col. Oriental, León, Gto., Mexico, C.P. 37510
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.
PROFESSORS AND COURSES:
Rick S. Blum (Lehigh University), [introductory/intermediate] Deep Learning and Cybersecurity
Ben Brown (Lawrence Berkeley National Laboratory), [introductory/advanced] Explainable AI (XAI) Techniques for Science and Engineering -- Toward Statistical Inference for the 21st Century
Georgios Giannakis (University of Minnesota), [advanced] Ensembles for Interactive and Deep Learning Machines with Scalability, Expressivity, and Adaptivity
Çağlar Gülçehre (DeepMind), [intermediate/advanced] Deep 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] Deep Learning and Statistics: Better Together
Abdelrahman Mohamed (Facebook AI Research), [introductory/advanced] Recent Advances in Automatic Speech Recognition
Jan Peters (Technical University of Darmstadt), [intermediate] Robot Learning
Massimiliano Pontil (Italian Institute of Technology), [intermediate/advanced] Statistical Learning Theory
Jose Principe (University of Florida), [intermediate/advanced] Cognitive Architectures for Object Recognition in Video
Fedor Ratnikov (National Research University Higher School of Economics), [introductory] Specifics of Applying Machine Learning to Problems in Natural Science
Salim Roukos (IBM Research AI), [intermediate/advanced] Deep Learning Methods for Natural Language Processing
Björn Schuller (Imperial College London), [introductory/intermediate] Deep Signal Processing
Alex Smola (Amazon), [introductory/advanced] Dive into Deep Learning
Sargur N. Srihari (University at Buffalo), [introductory] Generative Models in Deep Learning
Kunal Talwar (Google Brain), [intermediate] Differentially Private Machine Learning
René Vidal (Johns Hopkins University), [intermediate/advanced] Mathematics of Deep Learning
Haixun Wang (WeWork), [introductory/intermediate] Conceptual Understanding and Machine Learning
Ming-Hsuan Yang (University of California, Merced), [intermediate/advanced] Learning to Track Objects
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 19, 2020.
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 19, 2020.
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 19, 2020.
Teresa Efigenia Alarcón Martínez (Guadalajara)
Oscar Dalmau Cedeño (Guanajuato, co-chair)
Carlos Martín-Vide (Tarragona, program chair)
Sara Morales (Brussels)
Manuel J. Parra-Royón (Granada)
David Silva (London, co-chair)
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 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 is exhausted. It is highly 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 deadline.
Suggestions for accommodation will be available in due time.
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
Centro de Investigación en Matemáticas, A.C. (CIMAT-CONACyT) – Guanajuato
Centro Universitario de los Valles, Universidad de Guadalajara
Institute for Research Development, Training and Advice (IRDTA) – Brussels/London
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