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

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ELM 2021 — Extreme Learning Machines 2021
15. Dez 2021 - 16. Dez 2021 • Helsinki - VIRTUAL CONFERENCE, Finnland
Veranstalter:
Arcada University of Applied Sciences, Finland, and co‐organized by University of Houston, Texas, USA, and Mind PointEye, Singapore
Zusammenfassung:
VIRTUAL CONFERENCE on Extreme Learning Machines (ELM) aims to enable pervasive learning and pervasive intelligence. As advocated by ELM theories, it is exciting to see the convergence of machine learning and biological learning from the long-term point of view. ELM may be one of the fundamental `learning particles’ filling the gaps between machine learning and biological learning (of which activation functions are even unknown). ELM represents a suite of (machine and biological) learning techniques in which hidden neurons need not be tuned: inherited from their ancestors or randomly generated. ELM learning theories show that effective learning algorithms can be derived based on randomly generated hidden neurons (biological neurons, artificial neurons, wavelets, Fourier series, etc) as long as they are nonlinear piecewise continuous, independent of training data and application environments. Increasingly, evidence from neuroscience suggests that similar principles apply in biological learning systems. ELM theories and algorithms argue that “random hidden neurons” capture an essential aspect of biological learning mechanisms as well as the intuitive sense that the efficiency of biological learning need not rely on computing power of neurons. ELM theories thus hint at possible reasons why the brain is more intelligent and effective than current computers.
Kontakt:
ELM organizing committee;     Email: elm201x(at)gmail.com
Themen:
ELM, Hierarchical ELM, AI for IoT, Synergy of Machine Learning and Biological Learning
Einsendeschluss für Abstracts:
01. Nov 2021
Eintrags-ID:
1446489


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Stand vom 29. September 2021