Konferenzen zum Thema Neuronale Netze und Künstliche Intelligenz, Maschinelles Lernen in den Vereinigten Staaten (USA)

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1
AVWS1 — Workshop: Individual Vehicle Autonomy: Perception and Control
05. Okt 2020 - 09. Okt 2020 • Los Angeles, California, Vereinigte Staaten
Veranstalter:
IPAM
Zusammenfassung:
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).
Themen:
Part of the Long Program Mathematical Challenges and Opportunities for Autonomous Vehicles
Eintrags-ID:
1275173
2
IROS — IEEE/RSJ International Conference on Intelligent Robots and Systems
25. Okt 2020 - 29. Okt 2020 • Las Vegas, Vereinigte Staaten
Eintrags-ID:
1307182
3
ODSC West 2020
27. Okt 2020 - 30. Okt 2020 • Online, Vereinigte Staaten
Veranstalter:
ODSC
Zusammenfassung:
ODSC West 2020 is going virtual! We’re thrilled to be hosting our third virtual conference October 27th-30th. Featuring 100+ hands-on training sessions and workshops, 240 speakers, and 320 hours of content, ODSC West Virtual Conference is the perfect opportunity to gain new in-demand skills and network with your peers and our renowned speakers wherever you are. Get your pass today to save 70% on your ticket to ODSC West Virtual Conference. https://odsc.com/california/#register
Kontakt:
Tel.: [+1 510 984 8238];     Email: info@odsc.com
Themen:
Data Science, Artificial Intelligence, Machine Learning
Eintrags-ID:
1360616
Verwandte Fachgebiete:
4
NeurIPS 2020 — Thirty-fourth Conference on Neural Information Processing Systems
05. Dez 2020 - 12. Dez 2020 • Virtual-only Conference, Vereinigte Staaten
Zusammenfassung:
The purpose of the Neural Information Processing Systems annual meeting is to foster the exchange of research on neural information processing systems in their biological, technological, mathematical, and theoretical aspects. The core focus is peer-reviewed novel research which is presented and discussed in the general session, along with invited talks by leaders in their field. On Sunday is an Expo, where our top industry sponsors give talks, panels, demos, and workshops on topics that are of academic interest. On Monday are tutorials, which cover a broad background on current lines of inquiry, affinity group meetings, and the opening talk & reception. The general sessions are held Tuesday - Thursday, and include talks, posters, and demonstrations. Friday - Saturday are the workshops, which are smaller meetings focused on current topics, and provide an informal, cutting edge venue for discussion.
Eintrags-ID:
1372537
Webseite:
5
The Thirty-Third Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-21) Collocated with AAAI-21
04. Feb 2021 - 06. Feb 2021 • virtual, Vereinigte Staaten
Zusammenfassung:
The Thirty-Third Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-21) is a venue for papers describing highly innovative realizations of AI technology. The objective of the conference is to showcase successful applications and novel uses of AI. The conference will use technical papers, best practice papers, invited talks, and panel discussions to explore issues, methods, and lessons learned in the development and deployment of AI applications; and to promote an interchange of ideas between basic and applied AI and the discourse on the actual deployment of AI in practice.
Eintrags-ID:
1371582
6
Deep Learning and Combinatorial Optimization
22. Feb 2021 - 26. Feb 2021 • Los Angeles, CA, Vereinigte Staaten
Veranstalter:
Institute of Pure and Applied Mathematics (IPAM), UCLA
Zusammenfassung:
In recent years, deep learning has significantly improved the fields of computer vision, natural language processing and speech recognition. Beyond these traditional fields, deep learning has been expended to quantum chemistry, physics, neuroscience, and more recently to combinatorial optimization (CO). Well-known CO problems are Travelling Salesman Problem, assignment problems, routing, planning, Bayesian search, and scheduling. CO is basically used every day in finance and revenue management, transportation, manufacturing, supply chain, public policy, hardware design, computing and information technology. The workshop will bring together experts in mathematics (optimization, graph theory, sparsity, combinatorics, statistics), CO (assignment problems, routing, planning, Bayesian search, scheduling), machine learning (deep learning, supervised, self-supervised and reinforcement learning) and specific applicative domains (e.g. finance, transportation, hardware design, computing and information technology) to establish the current state of these emerging techniques and discuss the next directions. Besides, such generalization of deep learning techniques to CO problems will also push forward the mathematical analysis of the properties of these learning systems like generalization and transfer, stochastic optimization and dynamic predictivity that make the success of these techniques.
Eintrags-ID:
1375311
7
SEG Research Workshop: Data Analytics & Machine Learning for Exploration & Production
15. Mär 2021 - 18. Mär 2021 • Denver, Colorado, Vereinigte Staaten
Veranstalter:
SEG - Society of Exploration Geophysicists
Zusammenfassung:
The most significant contribution of this event is the Emergence of the utilization of data analytics and machine learning for geoscience. This workshop is designed to showcase the successes and challenges of practicing machine learning and data analytics in the geoscience domain to improve accuracy and efficiency of algorithms and/or workflows. For example, in addition to existing applications such as seismic geobody identification and well log data analysis, what other challenging geoscience problems can be formulated and solved effectively by machine learning? How can machine learning algorithms and workflows be tailored to meet the specific physical constraints of geoscience data? How can we fully exploit the power of machine learning and physics-based approaches?
Eintrags-ID:
1358238
Verwandte Fachgebiete:
8
Safety and Security of Deep Learning
10. Apr 2021 - 11. Apr 2021 • Providence, RI, Vereinigte Staaten
Veranstalter:
ICERM - The Institute for Computational and Experimental Research in Mathematics
Zusammenfassung:
Deep learning is profoundly reshaping the research directions of entire scientific communities across mathematics, computer science, and statistics, as well as the physical, biological and medical sciences . Yet, despite their indisputable success, deep neural networks are known to be universally unstable. That is, small changes in the input that are almost undetectable produce significant changes in the output. This happens in applications such as image recognition and classification, speech and audio recognition, automatic diagnosis in medicine, image reconstruction and medical imaging as well as inverse problems in general. This phenomenon is now very well documented and yields non-human-like behaviour of neural networks in the cases where they replace humans, and unexpected and unreliable behaviour where they replace standard algorithms in the sciences.
Kontakt:
Tel.: [4018635030];     Email: programstaff@icerm.brown.edu
Eintrags-ID:
1380385
Verwandte Fachgebiete:
9
Searches and Machine Learning Meet the Precision Frontier
12. Apr 2021 - 15. Apr 2021 • UC Santa Barbara, Vereinigte Staaten
Veranstalter:
Kavli Institute for Theoretical Physics (KITP)
Zusammenfassung:
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.
Eintrags-ID:
1246677
Verwandte Fachgebiete:
10
Workshop — Hot Topics: Topological Insights in Neuroscience
03. Mai 2021 - 07. Mai 2021 • Berkeley, Kalifornien, Vereinigte Staaten
Veranstalter:
MRSI – Mathematical Sciences Research Institute, Berkeley
Zusammenfassung:
The talks in this workshop will present a wide array of current applications of topology in neuroscience, including classification and synthesis of neuron morphologies, analysis of synaptic plasticity, algebraic analysis of the neural code, topological analysis of neural networks and their dynamics, topological decoding of neural activity, diagnosis of traumatic brain injuries, and topological biomarkers for psychiatric disease. Some of the talks will be devoted to promising new directions in algebraic topology that have been inspired by neuroscience.
Eintrags-ID:
1376592
Verwandte Fachgebiete:
11
Gordon Research Conference — Bioelectronics
06. Jun 2021 - 11. Jun 2021 • Proctor Academy, Andover, NH, Vereinigte Staaten
Eintrags-ID:
1318211


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Stand vom 24. September 2020