Hyperparameter optimization in learning systems

DOI10.1007/s41965-019-00023-0zbMath1469.68020OpenAlexW2981111316WikidataQ127001210 ScholiaQ127001210MaRDI QIDQ1983037

R. Andonie

Publication date: 14 September 2021

Published in: Journal of Membrane Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s41965-019-00023-0

zbMATH Keywords

machine learningmembrane computingP-systemneural computingspiking neural P-systemhyperparameters

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Biologically inspired models of computation (DNA computing, membrane computing, etc.) (68Q07)

Related Items (2)

Fine-Grained Job Salary Benchmarking with a Nonparametric Dirichlet Process–Based Latent Factor Model ⋮ A distributed adaptive optimization spiking neural P system for approximately solving combinatorial optimization problems

Uses Software

• LIBSVM
• WEKA
• Scikit
• Spearmint
• Hyperopt
• Auto-WEKA
• auto-sklearn
• FBNetV2

Cites Work

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• Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization
• Computing with membranes
• Spiking neural \(\mathrm{P}\) systems: theoretical results and applications
• Support-vector networks
• Adaptive P systems
• Adaptive fuzzy spiking neural P systems for fuzzy inference and learning
• Spiking Neural P Systems with Weights
• First draft of a report on the EDVAC
• 10.1162/153244303322753616
• Hebbian Learning from Spiking Neural P Systems View
• A Simplex Method for Function Minimization
• A logical calculus of the ideas immanent in nervous activity

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