Konferenzen zum Thema Neuronale Netze und Künstliche Intelligenz, Maschinelles Lernen in Kanada

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1
AIML — AI and ML Strategies Summit
15. Sep 2020 - 16. Sep 2020 • Toronto, Kanada
Veranstalter:
Strategy Institute
Zusammenfassung:
AI and Machine Learning have evolved from a "nice-to-have" to an imperative for all organizations across all industries within the last year. It is your turn to build an AI and Machine Learning strategy by learning about the latest technologies and implementations from high-profile companies. Over a course of two full days, learn from TD, Air Canada, Modiface, LG, and more about proven strategies and detailed action plans. Our events allow for valuable networking opportunities with business leaders from across North America. Registration is limited - save you spot and join us on Sept 15-16, 2020 in Toronto, ON.
Kontakt:
Customer Care;     Tel.: [1(866)298-9343 ext.259];     Email: customercare@strategyinstitute.com
Eintrags-ID:
1341523
2
NeurIPS 2020 — 34th Annual Conference on Neural Information Processing Systems
06. Dez 2020 - 12. Dez 2020 • Vancouver, Kanada
Zusammenfassung:
We invite submissions for the Thirty-Fourth Annual Conference on Neural Information Processing Systems (NeurIPS 2020), a multi-track, interdisciplinary conference that brings together researchers in machine learning, computational neuroscience, and their applications.
Eintrags-ID:
1359692
3
Continuum Models and Optimisation for Deep Neural Networks
10. Jan 2021 - 15. Jan 2021 • Banff Centre in Alberta, Kanada
Veranstalter:
Banff International Research Station for Mathematical Innovation and Discovery (BIRS)
Zusammenfassung:
Banff's new workshop on Continuum models and optimisation for deep neural networks brings together scientists to discuss the foundations of our digital revolution, and to investigate the reliability of their results. As often, mathematics is the fundamental tool to examine today's challenges. Mathematics structures knowledge and identifies the strengths and limitations of deep learning algorithms. A better understanding of the maths behind deep learning helps us to develop more efficient algorithms and to put safety critical industrial areas such as autonomous driving on a firm ground.
Eintrags-ID:
1364012
4
AAAI-21 — Thirty-Fifth AAAI Conference on Artificial Intelligence
02. Feb 2021 - 09. Feb 2021 • Vancouver, Kanada
Veranstalter:
Association for the Advancement of Artificial Intelligence (AAAI)
Zusammenfassung:
The purpose of the AAAI conference is to promote research in artificial intelligence (AI) and scientific exchange among AI researchers, practitioners, scientists, and engineers in affiliated disciplines.
Eintrags-ID:
1359378
5
Advances in Stein’s Method and its Applications in Machine Learning and Optimization
11. Apr 2021 - 16. Apr 2021 • Banff Centre in Alberta, Kanada
Veranstalter:
Banff International Research Station for Mathematical Innovation and Discovery (BIRS)
Zusammenfassung:
Recently a variety of state-of-the-art methods in machine learning and artificial intelligence have been developed motivated by techniques from Stein’s method, a successful tool from the field of probability theory. These methods have enabled efficient analysis of the large amounts of data being produced in several scientific fields, like neuroscience, information technology, and finance. Motivated by this success, there has been an ever increasing interest in exploring further connections between Stein’s method and machine learning. The focus of this workshop is to consolidate isolated efforts and develop a theoretically principled inferential and computational framework via Stein's method for analyzing increasingly complex models and data objects. This workshop is intended to bring together prominent and promising young and diverse researchers working on Stein’s method and machine learning, and to charter the path for future development in the field.
Eintrags-ID:
1364207
6
Mathematical Statistics and Learning
28. Nov 2021 - 03. Dez 2021 • Banff Centre in Alberta, Kanada
Veranstalter:
Banff International Research Station for Mathematical Innovation and Discovery (BIRS)
Zusammenfassung:
The workshop focuses on the novel mathematical challenges of statistics and machine learning. The spectacular success of machine learning in a wide range of applications opens many exciting theoretical challenges in a number of mathematical fields, including probability, statistics, combinatorics, optimization, and geometry. BIRS will bring together researchers of machine learning and mathematical statistics to discuss these problems. The principal topics include combinatorial statistics, online learning, and deep neural networks.
Eintrags-ID:
1364506


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Stand vom 11. August 2020