Obey validity limits of data-driven models through topological data analysis and one-class classification

DOI10.1007/s11081-021-09608-0zbMath1494.90088OpenAlexW3163196550MaRDI QIDQ2147924

Linus Netze, Artur M. Schweidtmann, Christian Wende, Jana M. Weber, Alexander Mitsos

Publication date: 20 June 2022

Published in: Optimization and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11081-021-09608-0

zbMATH Keywords

deterministic global optimizationtopological data analysispersistent homologymachine-learningone-class support vector machine

Mathematics Subject Classification ID

Applications of mathematical programming (90C90) Nonconvex programming, global optimization (90C26)

Related Items (3)

Surrogate-based branch-and-bound algorithms for simulation-based black-box optimization ⋮ Convex and concave envelopes of artificial neural network activation functions for deterministic global optimization ⋮ MeLOn

Uses Software

• Pyomo
• SciPy
• libMC
• Scikit
• Python
• jHoles
• Keras
• MAiNGO
• Ripser.py
• EAGO.jl

Cites Work

• Unnamed Item
• jHoles: a tool for understanding biological complex networks via clique weight rank persistent homology
• Soft sensors for monitoring and control of industrial processes.
• A reduced space branch and bound algorithm for global optimization.
• Deterministic global optimization of process flowsheets in a reduced space using McCormick relaxations
• Persistent homology over directed acyclic graphs
• Deterministic global optimization with artificial neural networks embedded
• Computing persistent homology
• A polyhedral branch-and-cut approach to global optimization
• Topological persistence and simplification
• Support-vector networks
• Deterministic global optimization with Gaussian processes embedded
• Data-driven construction of convex region surrogate models
• Chance-Constrained Programming
• McCormick-Based Relaxations of Algorithms
• EAGO.jl: easy advanced global optimization in Julia
• $P$-persistent homology of finite topological spaces
• Visualizing Sparse Filtrations.
• Pyomo -- optimization modeling in Python

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