Meetings/Workshops on Neural Networks and Artificial Intelligence, Machine Learning in the United States (USA)
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27 Apr 2020 - 30 Apr 2020 • New York, NY, United States
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Hot Topics: Optimal transport and applications to machine learning and statistics
04 May 2020 - 08 May 2020 • Berkeley, California, United States
Mathematical Sciences Research Institute (MSRI)
The goal of the workshop is to explore the many emerging connections between the theory of Optimal Transport and models and algorithms currently used in the Machine Learning community. In particular, the use of Wasserstein metrics and the relation between discrete models and their continuous counterparts will be presented and discussed.
AVWS1 — Workshop: Individual Vehicle Autonomy: Perception and Control
05 Oct 2020 - 09 Oct 2020 • Los Angeles, California, United States
This workshop will bring together researchers working on the theoretical sides of deep learning techniques for perception and control of automated vehicles with researchers interested in assuring these autonomous systems operate with safety guarantees. Moreover, experts in sensing and imaging technology will be brought to the table, to cover the full pipeline from the collection of the data, over the AI theory and development, all the way to the software and actuation challenges. Additional themes addressed in this workshop include interactions between vehicle sensing and the infrastructure, and cybersecurity aspects related to sensing and machine learning (how to purposefully mislead sensors and AI).
Part of the Long Program Mathematical Challenges and Opportunities for Autonomous Vehicles
IROS — IEEE/RSJ International Conference on Intelligent Robots and Systems
25 Oct 2020 - 29 Oct 2020 • Las Vegas, United States
Searches and Machine Learning Meet the Precision Frontier
12 Apr 2021 - 15 Apr 2021 • UC Santa Barbara, United States
Kavli Institute for Theoretical Physics (KITP)
The Large Hadron Collider (LHC) is the world’s facility for probing fundamental physics at the electroweak scale and well beyond. As it enters a new phase of extended data accumulation, two broad challenges emerge: how to fulfill the potential for percent-level precision with the large dataset, and how to maximise the information that can be extracted from each event about the underlying scattering process, in particular with machine learning. Solving these problems will have an impact across a wide range of physics topics: establishing the properties of the newly discovered interactions of the Higgs sector and understanding electroweak symmetry breaking, enhancing the sensitivity of searches for physics beyond the Standard Model (BSM), and precision measurements of a range of fundamental parameters in the Standard Model.
Gordon Research Conference — Bioelectronics
06 Jun 2021 - 11 Jun 2021 • Proctor Academy, Andover, NH, United States
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Last updated: 20 January 2020