b'Thomas B\xc3\xa4ck'

research

∙ 09/05/2023

MA-VAE: Multi-head Attention-based Variational Autoencoder Approach for Anomaly Detection in Multivariate Time-series Applied to Automotive Endurance Powertrain Testing

A clear need for automatic anomaly detection applied to automotive testi...

0 Lucas Correia, et al. ∙

research

∙ 07/19/2023

Adversarial Latent Autoencoder with Self-Attention for Structural Image Synthesis

Generative Engineering Design approaches driven by Deep Generative Model...

0 Jiajie Fan, et al. ∙

research

∙ 06/18/2023

MA-BBOB: Many-Affine Combinations of BBOB Functions for Evaluating AutoML Approaches in Noiseless Numerical Black-Box Optimization Contexts

Extending a recent suggestion to generate new instances for numerical bl...

0 Diederick Vermetten, et al. ∙

research

∙ 06/05/2023

Representation-agnostic distance-driven perturbation for optimizing ill-conditioned problems

Locality is a crucial property for efficiently optimising black-box prob...

0 Kirill Antonov, et al. ∙

research

∙ 05/24/2023

Challenges of ELA-guided Function Evolution using Genetic Programming

Within the optimization community, the question of how to generate new o...

0 Fu Xing Long, et al. ∙

research

∙ 04/25/2023

When to be Discrete: Analyzing Algorithm Performance on Discretized Continuous Problems

The domain of an optimization problem is seen as one of its most importa...

0 André Thomaser, et al. ∙

research

∙ 03/31/2023

DoE2Vec: Deep-learning Based Features for Exploratory Landscape Analysis

We propose DoE2Vec, a variational autoencoder (VAE)-based methodology to...

0 Bas van Stein, et al. ∙

research

∙ 03/08/2023

Towards Self-adaptive Mutation in Evolutionary Multi-Objective Algorithms

Parameter control has succeeded in accelerating the convergence process ...

0 Furong Ye, et al. ∙

research

∙ 02/02/2023

Benchmarking Algorithms for Submodular Optimization Problems Using IOHProfiler

Submodular functions play a key role in the area of optimization as they...

0 Frank Neumann, et al. ∙

research

∙ 12/13/2022

Multi-surrogate Assisted Efficient Global Optimization for Discrete Problems

Decades of progress in simulation-based surrogate-assisted optimization ...

0 Qi Huang, et al. ∙

research

∙ 12/07/2022

A Decision Diagram Operation for Reachability

Saturation is considered the state-of-the-art method for computing fixpo...

0 Sebastiaan Brand, et al. ∙

research

∙ 11/14/2022

Optimizing Stimulus Energy for Cochlear Implants with a Machine Learning Model of the Auditory Nerve

Performing simulations with a realistic biophysical auditory nerve fiber...

0 Jacob de Nobel, et al. ∙

research

∙ 10/30/2022

Saliency Can Be All You Need In Contrastive Self-Supervised Learning

We propose an augmentation policy for Contrastive Self-Supervised Learni...

0 Veysel Kocaman, et al. ∙

research

∙ 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...

5 Alexander Zeiser, et al. ∙

research

∙ 07/13/2022

Reinforcement Learning Assisted Recursive QAOA

Variational quantum algorithms such as the Quantum Approximation Optimiz...

0 Yash J. Patel, et al. ∙

research

∙ 06/22/2022

Optimally Weighted Ensembles of Regression Models: Exact Weight Optimization and Applications

Automated model selection is often proposed to users to choose which mac...

0 Patrick Echtenbruck, et al. ∙

research

∙ 06/21/2022

Quantum-Enhanced Selection Operators for Evolutionary Algorithms

Genetic algorithms have unique properties which are useful when applied ...

0 David Von Dollen, et al. ∙

research

∙ 06/20/2022

Hyperparameter Importance of Quantum Neural Networks Across Small Datasets

As restricted quantum computers are slowly becoming a reality, the searc...

0 Charles Moussa, et al. ∙

research

∙ 05/12/2022

Equivariant quantum circuits for learning on weighted graphs

Variational quantum algorithms are the leading candidate for near-term a...

8 Andrea Skolik, et al. ∙

research

∙ 04/20/2022

Analyzing the Impact of Undersampling on the Benchmarking and Configuration of Evolutionary Algorithms

The stochastic nature of iterative optimization heuristics leads to inhe...

10 Diederick Vermetten, et al. ∙

research

∙ 04/13/2022

Chaining of Numerical Black-box Algorithms: Warm-Starting and Switching Points

Dynamic algorithm selection can be beneficial for solving numerical blac...

27 Dominik Schröder, et al. ∙

research

∙ 03/24/2022

Explainable Artificial Intelligence for Exhaust Gas Temperature of Turbofan Engines

Data-driven modeling is an imperative tool in various industrial applica...

0 Marios Kefalas, et al. ∙

research

∙ 03/17/2022

Non-Elitist Selection among Survivor Configurations can Improve the Performance of Irace

Modern optimization strategies such as evolutionary algorithms, ant colo...

0 Furong Ye, et al. ∙

research

∙ 11/07/2021

IOHexperimenter: Benchmarking Platform for Iterative Optimization Heuristics

We present IOHexperimenter, the experimentation module of the IOHprofile...

0 Jacob de Nobel, et al. ∙

research

∙ 08/19/2021

Lifelong Computing

Computing systems form the backbone of many aspects of our life, hence t...

0 Danny Weyns, et al. ∙

research

∙ 06/29/2021

Multiagent Deep Reinforcement Learning: Challenges and Directions Towards Human-Like Approaches

This paper surveys the field of multiagent deep reinforcement learning. ...

0 Annie Wong, et al. ∙

research

∙ 06/11/2021

Automated Configuration of Genetic Algorithms by Tuning for Anytime Performance

Finding the best configuration of algorithms' hyperparameters for a give...

13 Furong Ye, et al. ∙

research

∙ 05/21/2021

Addressing the Multiplicity of Solutions in Optical Lens Design as a Niching Evolutionary Algorithms Computational Challenge

Optimal Lens Design constitutes a fundamental, long-standing real-world ...

0 Anna V. Kononova, et al. ∙

research

∙ 05/10/2021

Is there Anisotropy in Structural Bias?

Structural Bias (SB) is an important type of algorithmic deficiency with...

7 Diederick Vermetten, et al. ∙

research

∙ 05/10/2021

Designing Air Flow with Surrogate-assisted Phenotypic Niching

In complex, expensive optimization domains we often narrowly focus on fi...

0 Alexander Hagg, et al. ∙

research

∙ 05/10/2021

An Analysis of Phenotypic Diversity in Multi-Solution Optimization

More and more, optimization methods are used to find diverse solution se...

0 Alexander Hagg, et al. ∙

research

∙ 05/10/2021

Expressivity of Parameterized and Data-driven Representations in Quality Diversity Search

We consider multi-solution optimization and generative models for the ge...

28 Alexander Hagg, et al. ∙

research

∙ 04/16/2021

Explorative Data Analysis of Time Series based AlgorithmFeatures of CMA-ES Variants

In this study, we analyze behaviours of the well-known CMA-ES by extract...

31 Jacob de Nobel, et al. ∙

research

∙ 04/08/2021

Quantum-Assisted Feature Selection for Vehicle Price Prediction Modeling

Within machine learning model evaluation regimes, feature selection is a...

19 David Von Dollen, et al. ∙

research

∙ 03/25/2021

Robust subgroup discovery

We introduce the problem of robust subgroup discovery, i.e., finding a s...

0 Hugo Manuel Proença, et al. ∙

research

∙ 03/11/2021

Preprint: Norm Loss: An efficient yet effective regularization method for deep neural networks

Convolutional neural network training can suffer from diverse issues lik...

0 Theodoros Georgiou, et al. ∙

research

∙ 03/11/2021

PREPRINT: Comparison of deep learning and hand crafted features for mining simulation data

Computational Fluid Dynamics (CFD) simulations are a very important tool...

0 Theodoros Georgiou, et al. ∙

research

∙ 03/04/2021

Finding Efficient Trade-offs in Multi-Fidelity Response Surface Modeling

In the context of optimization approaches to engineering applications, t...

0 Sander van Rijn, et al. ∙

research

∙ 02/25/2021

Tuning as a Means of Assessing the Benefits of New Ideas in Interplay with Existing Algorithmic Modules

Introducing new algorithmic ideas is a key part of the continuous improv...

6 Jacob de Nobel, et al. ∙

research

∙ 02/12/2021

Leveraging Benchmarking Data for Informed One-Shot Dynamic Algorithm Selection

A key challenge in the application of evolutionary algorithms in practic...

0 Furong Ye, et al. ∙

research

∙ 02/06/2021

Learning adaptive differential evolution algorithm from optimization experiences by policy gradient

Differential evolution is one of the most prestigious population-based s...

0 Jianyong Sun, et al. ∙

research

∙ 11/12/2020

Improving Model Accuracy for Imbalanced Image Classification Tasks by Adding a Final Batch Normalization Layer: An Empirical Study

Some real-world domains, such as Agriculture and Healthcare, comprise ea...

0 Veysel Kocaman, et al. ∙

research

∙ 11/01/2020

Neural Network Design: Learning from Neural Architecture Search

Neural Architecture Search (NAS) aims to optimize deep neural networks' ...

142 Bas van Stein, et al. ∙

research

∙ 07/08/2020

IOHanalyzer: Performance Analysis for Iterative Optimization Heuristic

We propose IOHanalyzer, a new software for analyzing the empirical perfo...

4 Hao Wang, et al. ∙

research

∙ 06/21/2020

A Modular Hybridization of Particle Swarm Optimization and Differential Evolution

In swarm intelligence, Particle Swarm Optimization (PSO) and Differentia...

11 Rick Boks, et al. ∙

research

∙ 06/16/2020

Discovering outstanding subgroup lists for numeric targets using MDL

The task of subgroup discovery (SD) is to find interpretable description...

0 Hugo Manuel Proença, et al. ∙

research

∙ 06/11/2020

Towards Dynamic Algorithm Selection for Numerical Black-Box Optimization: Investigating BBOB as a Use Case

One of the most challenging problems in evolutionary computation is to s...

3 Diederick Vermetten, et al. ∙

research

∙ 06/10/2020

Benchmarking a (μ+λ) Genetic Algorithm with Configurable Crossover Probability

We investigate a family of (μ+λ) Genetic Algorithms (GAs) which creates ...

3 Furong Ye, et al. ∙

research

∙ 04/22/2020

Differential evolution outside the box

This paper investigates how often the popular configurations of Differen...

0 Anna V. Kononova, et al. ∙

research

∙ 04/15/2020

Improving Many-objective Evolutionary Algorithms by Means of Expanded Cone Orders

Given a point in m-dimensional objective space, the local environment of...

0 Yali Wang, et al. ∙

Thomas Bäck

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