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06/30/2023
Comparing Algorithm Selection Approaches on Black-Box Optimization Problems
Performance complementarity of solvers available to tackle black-box opt...
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06/01/2023
Algorithm Instance Footprint: Separating Easily Solvable and Challenging Problem Instances
In black-box optimization, it is essential to understand why an algorith...
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05/15/2023
Artificial intelligence to advance Earth observation: a perspective
Earth observation (EO) is a prime instrument for monitoring land and oce...
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05/03/2023
Automated Scientific Discovery: From Equation Discovery to Autonomous Discovery Systems
The paper surveys automated scientific discovery, from equation discover...
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02/20/2023
Efficient Generator of Mathematical Expressions for Symbolic Regression
We propose an approach to symbolic regression based on a novel variation...
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01/24/2023
Using Knowledge Graphs for Performance Prediction of Modular Optimization Algorithms
Empirical data plays an important role in evolutionary computation resea...
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11/23/2022
FAIRification of MLC data
The multi-label classification (MLC) task has increasingly been receivin...
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11/21/2022
Explainable Model-specific Algorithm Selection for Multi-Label Classification
Multi-label classification (MLC) is an ML task of predictive modeling in...
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07/19/2022
Semi-supervised Predictive Clustering Trees for (Hierarchical) Multi-label Classification
Semi-supervised learning (SSL) is a common approach to learning predicti...
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04/15/2022
The Importance of Landscape Features for Performance Prediction of Modular CMA-ES Variants
Selecting the most suitable algorithm and determining its hyperparameter...
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03/04/2022
Boosting the Performance of Quantum Annealers using Machine Learning
Noisy intermediate-scale quantum (NISQ) devices are spearheading the sec...
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11/25/2021
Unsupervised Feature Ranking via Attribute Networks
The need for learning from unlabeled data is increasing in contemporary ...
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08/03/2021
GalaxAI: Machine learning toolbox for interpretable analysis of spacecraft telemetry data
We present GalaxAI - a versatile machine learning toolbox for efficient ...
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06/28/2021
Explaining the Performance of Multi-label Classification Methods with Data Set Properties
Meta learning generalizes the empirical experience with different learni...
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04/24/2021
OPTION: OPTImization Algorithm Benchmarking ONtology
Many platforms for benchmarking optimization algorithms offer users the ...
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02/14/2021
Comprehensive Comparative Study of Multi-Label Classification Methods
Multi-label classification (MLC) has recently received increasing intere...
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01/23/2021
ReliefE: Feature Ranking in High-dimensional Spaces via Manifold Embeddings
Feature ranking has been widely adopted in machine learning applications...
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12/01/2020
Probabilistic Grammars for Equation Discovery
Equation discovery, also known as symbolic regression, is a type of auto...
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11/23/2020
Ensemble- and Distance-Based Feature Ranking for Unsupervised Learning
In this work, we propose two novel (groups of) methods for unsupervised ...
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08/10/2020
Feature Ranking for Semi-supervised Learning
The data made available for analysis are becoming more and more complex ...
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06/22/2020
Multi-view redescription mining using tree-based multi-target prediction models
The task of redescription mining is concerned with re-describing differe...
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02/11/2020
Feature Importance Estimation with Self-Attention Networks
Black-box neural network models are widely used in industry and science,...
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07/01/2019
Equation Discovery for Nonlinear System Identification
Equation discovery methods enable modelers to combine domain-specific kn...
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06/21/2019
Meta-Model Framework for Surrogate-Based Parameter Estimation in Dynamical Systems
The central task in modeling complex dynamical systems is parameter esti...
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09/03/2018
Machine learning for predicting thermal power consumption of the Mars Express Spacecraft
The thermal subsystem of the Mars Express (MEX) spacecraft keeps the on-...
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04/17/2018
MetaBags: Bagged Meta-Decision Trees for Regression
Ensembles are popular methods for solving practical supervised learning ...
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02/20/2017
Using Redescription Mining to Relate Clinical and Biological Characteristics of Cognitively Impaired and Alzheimer's Disease Patients
We used redescription mining to find interpretable rules revealing assoc...
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06/13/2016
