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03/31/2023
DoE2Vec: Deep-learning Based Features for Exploratory Landscape Analysis
We propose DoE2Vec, a variational autoencoder (VAE)-based methodology to...
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12/13/2022
Multi-surrogate Assisted Efficient Global Optimization for Discrete Problems
Decades of progress in simulation-based surrogate-assisted optimization ...
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11/29/2022
BBOB Instance Analysis: Landscape Properties and Algorithm Performance across Problem Instances
Benchmarking is a key aspect of research into optimization algorithms, a...
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09/21/2022
Deep Learning based pipeline for anomaly detection and quality enhancement in industrial binder jetting processes
Anomaly detection describes methods of finding abnormal states, instance...
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03/24/2022
Explainable Artificial Intelligence for Exhaust Gas Temperature of Turbofan Engines
Data-driven modeling is an imperative tool in various industrial applica...
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01/17/2022
Using Machine Learning to Detect Rotational Symmetries from Reflectional Symmetries in 2D Images
Automated symmetry detection is still a difficult task in 2021. However,...
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05/10/2021
Emergence of Structural Bias in Differential Evolution
Heuristic optimisation algorithms are in high demand due to the overwhel...
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11/01/2020
Neural Network Design: Learning from Neural Architecture Search
Neural Architecture Search (NAS) aims to optimize deep neural networks' ...
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04/14/2020
A Tailored NSGA-III Instantiation for Flexible Job Shop Scheduling
A customized multi-objective evolutionary algorithm (MOEA) is proposed f...
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10/10/2018
Automatic Configuration of Deep Neural Networks with EGO
Designing the architecture for an artificial neural network is a cumbers...
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02/04/2017
Cluster-based Kriging Approximation Algorithms for Complexity Reduction
Kriging or Gaussian Process Regression is applied in many fields as a no...
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11/01/2016