Deep NeuroEvolution Workshop @ LOD 2019
5thInternational Conference on machine Learning, Optimization & Data science LOD, September 10-13, Siena (Tuscany) Italy
lod@icas.xyz
Deep NeuroEvolution: A Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning
The quest to evolve and optimize artificial neural networks through evolutionary computation.
https://www.oreilly.com/ideas/neuroevolution-a-different-kind-of-deep-learni...
In last two years, the use of deep neuroevolution has enabled researchers to extend reinforcement learning techniques to solve increasingly complex learning tasks. The emerging field of deep neuroevolution has led to remarkable empirical results in rich and varied domains like strategy games and robotics. This workshop will bring together researchers working at the intersection of deep learning, evolutionary computation, optimization and reinforcement learning, and it will help interested researchers outside of the field gain a high-level view about the current state of the art and potential directions for future contributions.
Submit your Deep Neuroevolution Paper by May 31
https://easychair.org/conferences/?conf=lod2019
Moreover, LOD 2019 is a great opportunity to present your work and congregate with leaders and experts in the Deep Learning, Optimization and Big Data. Feel free to check out our keynote speakers:
· Michael Bronstein, Imperial College London, UK
· Marco Gori, University of Siena, Italy
· Arthur Gretton, UCL, UK
· Arthur Guez Google DeepMind, Montreal, UK
· Kaisa Miettinen, University of Jyväskylä, Finland
· Jan Peters, Technische Universitaet Darmstadt
· Mauricio Resende, Amazon, USA
· Richard E. Turner, University of Cambridge, UK
Submit your Paper by May 31
https://easychair.org/conferences/?conf=lod2019
· Late Breaking Papers
· Poster Presentation
· Talk
· Deep Neuroevolution Workshop
LOD 2019 will focus on advances in science, technology and applications in the fields of Machine Learning, Data Science and Optimization.
Sessions
· LOD 2019 Big-Data Challenge: Our sponsor, Neodata Lab, will offer a prize of €2000 to the applicant who develops the most accurate algorithm to process an “approximate SQL-like query answering system” on a real dataset.
· Multi-Task Learning
· Reinforcement Learning
· Deep Learning
· Generative Adversarial Networks
· Deep Neuroevolution
· Networks with Memory
· Learning from Less Data and Building Smaller Models
· Simulation Environments to understand how AI Systems Learn
· Chatbots and Conversational Agents
· Data Science at Scale & Data in the Cloud
· Urban Informatics & Data-Driven Modelling of Complex Systems
· Data-centric Engineering
· Data Security, Traceability of Information & GDPR
· Economic Data Science
See you in Siena in September!
lod@icas.xyz