NextGen Synergy: Control Theory and Machine Learning

Name: NextGen Synergy: Control Theory and Machine Learning
Start: 2026-04-27T08:30:00+02:00
End: 2026-04-30T20:00:00+02:00
Location: Faculty of Economics and Management, Czech University of Life Sciences

Apr 27 – 30, 2026

Faculty of Economics and Management, Czech University of Life Sciences

Europe/Prague timezone

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klepkova@utia.cas.cz

Cone-Constrained Neural Networks for Structured Learning and Control

Apr 29, 2026, 5:40 PM

Accept as Poster presentation with Reimbursement Control Theory for Machine Learning Poster Session B

Affiliation of the corresponding author	Nicolaus Copernicus University in Toruń
Keywords	cone-constrained neural networks, monotone operators, fixed-point theory, autoencoders, second-order cones
Preferred type of presentation	Poster
Are you a member of COST Action CA24136?	Yes, I am a member of COST Action CA24136.
Are you applying for reimbursement?	Yes, I am applying for reimbursement

Krzysztof Rykaczewski (Nicolaus Copernicus University in Toruń, Poland) Grzegorz Gabor Michał Balicki Dr Piotr Przymus

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NextGen Synergy: Control Theory and Machine Learning

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Cone-Constrained Neural Networks for Structured Learning and Control

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NextGen Synergy: Control Theory and Machine Learning

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