All Stories

  1. Latest Approaches in Reasoning Large Language Models
  2. LLaMEA: Automatically Generating Metaheuristics with Large Language Models
  3. BLADE: Benchmark suite for LLM-driven Automated Design and Evolution of iterative optimisation heuristics
  4. Explainable Benchmarking for Iterative Optimization Heuristics
  5. Neighborhood Adaptive Differential Evolution
  6. Structural bias in optimization algorithms
  7. Optimizing Photonic Structures with Large Language Model Driven Algorithm Discovery
  8. Code Evolution Graphs: Understanding Large Language Model Driven Design of Algorithms
  9. Explainable Benchmarking for Iterative Optimization Heuristics
  10. In-the-loop Hyper-Parameter Optimization for LLM-Based Automated Design of Heuristics
  11. LLaMEA: A Large Language Model Evolutionary Algorithm for Automatically Generating Metaheuristics
  12. Stalling in Space: Attractor Analysis for Any Algorithm
  13. Controlling the Mutation in Large Language Models for the Efficient Evolution of Algorithms
  14. XAI for Benchmarking Black-Box Metaheuristics
  15. A Functional Analysis Approach to Symbolic Regression
  16. A Corridor Model Evolutionary Algorithm for Fast Converging Green Vehicle Routing Problem
  17. A Critical Analysis of Raven Roost Optimization
  18. Modular Optimization Framework for Mixed Expensive and Inexpensive Real-World Problems
  19. Hot off the Press: Parallel Multi-Objective Optimization for Expensive and Inexpensive Objectives and Constraints
  20. Landscape Analysis Based vs. Domain-Specific Optimization for Engineering Design Applications: A Clear Case
  21. Quality-diversity driven robust evolutionary optimization of optical designs
  22. Parallel multi-objective optimization for expensive and inexpensive objectives and constraints
  23. Generating Cheap Representative Functions for Expensive Automotive Crashworthiness Optimization
  24. A Deep Dive Into Effects of Structural Bias on CMA-ES Performance Along Affine Trajectories
  25. Evolutionary Computation and Explainable AI: A Roadmap to Understandable Intelligent Systems
  26. TX-Gen: Multi-Objective Optimization for Sparse Counterfactual Explanations for Time-Series Classification
  27. Towards Fairness in Machine Learning: Balancing Racially Imbalanced Datasets Through Data Augmentation and Generative AI
  28. Beyond the Veil of Similarity: Quantifying Semantic Continuity in Explainable AI
  29. Landscape-Aware Automated Algorithm Configuration Using Multi-output Mixed Regression and Classification
  30. Clustering-based Domain-Incremental Learning
  31. Curing ill-Conditionality via Representation-Agnostic Distance-Driven Perturbations
  32. New solutions to Cooke triplet problem via analysis of attraction basins
  33. DoE2Vec: Deep-learning Based Features for Exploratory Landscape Analysis
  34. Deep BIAS: Detecting Structural Bias using Explainable AI
  35. AI for Expensive Optimization Problems in Industry
  36. Application of Functional Kernel Hypothesis Testing for Channel Selection in Time Series Classification
  37. Evaluation of deep unsupervised anomaly detection methods with a data-centric approach for on-line inspection
  38. BBOB Instance Analysis: Landscape Properties and Algorithm Performance Across Problem Instances
  39. Challenges of ELA-Guided Function Evolution Using Genetic Programming
  40. A data-centric approach to anomaly detection in layer-based additive manufacturing
  41. Evolutionary Algorithms for Parameter Optimization—Thirty Years Later
  42. The Opaque Nature of Intelligence and the Pursuit of Explainable AI
  43. Multi-surrogate Assisted Efficient Global Optimization for Discrete Problems
  44. BIAS: A Toolbox for Benchmarking Structural Bias in the Continuous Domain
  45. GSAreport: Easy to Use Global Sensitivity Reporting
  46. A Comparison of Global Sensitivity Analysis Methods for Explainable AI with an Application in Genomic Prediction
  47. A Comparison of Global Sensitivity Analysis Methods for Explainable AI with an Application in Genomic Prediction
  48. Analysis of how bias in search algorithms can affect the search behaviour
  49. Exploratory Landscape Analysis in Real-World Engineering Optimization
  50. Multi-point acquisition function for constraint parallel efficient multi-objective optimization
  51. End-to-End Pipeline for Uncertainty Quantification and Remaining Useful Life Estimation: An Application on Aircraft Engines
  52. Explainable Artificial Intelligence for Exhaust Gas Temperature of Turbofan Engines
  53. Constrained Multi-Objective Optimization with a Limited Budget of Function Evaluations
  54. Multitask Shape Optimization Using a 3-D Point Cloud Autoencoder as Unified Representation
  55. Optimally Weighted Ensembles for Efficient Multi-objective Optimization
  56. Analysis of Structural Bias in Differential Evolution Configurations
  57. A Comparison of many Global Sensitivity Analysis methods
  58. Exploiting Generative Models for Performance Predictions of 3D Car Designs
  59. Using Machine Learning to Detect Rotational Symmetries from Reflectional Symmetries in 2D Images
  60. Point2FFD: Learning Shape Representations of Simulation-Ready 3D Models for Engineering Design Optimization
  61. BIAS: A Toolbox for Benchmarking Structural Bias in the Continuous Domain
  62. BIAS: A Toolbox for Benchmarking Structural Bias in the Continuous Domain
  63. Emergence of structural bias in differential evolution
  64. Exploiting Local Geometric Features in Vehicle Design Optimization with 3D Point Cloud Autoencoders
  65. SAMO-COBRA: A Fast Surrogate Assisted Constrained Multi-objective Optimization Algorithm
  66. Requirements towards optimizing analytics in industrial processes
  67. A Tailored NSGA-III for Multi-objective Flexible Job Shop Scheduling
  68. Back To Meshes: Optimal Simulation-ready Mesh Prototypes For Autoencoder-based 3D Car Point Clouds
  69. Neural Network Design: Learning from Neural Architecture Search
  70. Improving NSGA-III for flexible job shop scheduling using automatic configuration, smart initialization and local search
  71. Feature Visualization for 3D Point Cloud Autoencoders
  72. A New Approach Towards the Combined Algorithm Selection and Hyper-parameter Optimization Problem
  73. On the Efficiency of a Point Cloud Autoencoder as a Geometric Representation for Shape Optimization
  74. Scalability of Learning Tasks on 3D CAE Models Using Point Cloud Autoencoders
  75. Cluster-based Kriging approximation algorithms for complexity reduction
  76. Automatic Configuration of Deep Neural Networks with Parallel Efficient Global Optimization
  77. Designing Ships Using Constrained Multi-objective Efficient Global Optimization
  78. A Novel Uncertainty Quantification Method for Efficient Global Optimization
  79. A multi-method simulation of a high-frequency bus line
  80. A new acquisition function for Bayesian optimization based on the moment-generating function
  81. Algorithm configuration data mining for CMA evolution strategies
  82. Time complexity reduction in efficient global optimization using cluster kriging
  83. A framework for evaluating meta-models for simulation-based optimisation
  84. Local subspace-based outlier detection using global neighbourhoods
  85. Towards Data Driven Process Control in Manufacturing Car Body Parts
  86. Fuzzy clustering for Optimally Weighted Cluster Kriging
  87. An Incremental Algorithm for Repairing Training Sets with Missing Values
  88. Analysis and Visualization of Missing Value Patterns
  89. Optimally Weighted Cluster Kriging for Big Data Regression
  90. Fitness Landscape Analysis of NK Landscapes and Vehicle Routing Problems by Expanded Barrier Trees