Papers Evolutionary Algorithms
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An Analysis of the Preferences of Distribution Indicators in Evolutionary Multi-Objective Optimization
The distribution of objective vectors in a Pareto Front Approximation (PFA) is crucial for representing the associated manifold accurately. Distribution Indicators (DIs) assess the distribution of a PFA numerically, util…
DiversityEvolutionary AlgorithmsEvolutionary Optimization of Model Merging Recipes
Large language models (LLMs) have become increasingly capable, but their development often requires substantial computational resources. While model merging has emerged as a cost-effective promising approach for creating…
Evolutionary AlgorithmsMathmodelLLM Guided Evolution - The Automation of Models Advancing Models
In the realm of machine learning, traditional model development and automated approaches like AutoML typically rely on layers of abstraction, such as tree-based or Cartesian genetic programming. Our study introduces "Gui…
AutoMLDecision MakingEvolutionary AlgorithmsAn upper bound of the mutation probability in the genetic algorithm for general 0-1 knapsack problem
As an important part of genetic algorithms (GAs), mutation operators is widely used in evolutionary algorithms to solve $\mathcal{NP}$-hard problems because it can increase the population diversity of individual. Due to …
DiversityEvolutionary AlgorithmsMathPMBO: Enhancing Black-Box Optimization through Multivariate Polynomial Surrogates
We introduce a surrogate-based black-box optimization method, termed Polynomial-model-based optimization (PMBO). The algorithm alternates polynomial approximation with Bayesian optimization steps, using Gaussian processe…
Bayesian OptimizationEvolutionary AlgorithmsGaussian ProcessesQubit-Wise Architecture Search Method for Variational Quantum Circuits
Considering the noise level limit, one crucial aspect for quantum machine learning is to design a high-performing variational quantum circuit architecture with small number of quantum gates. As the classical neural archi…
Evolutionary AlgorithmsNeural Architecture SearchQuantum Machine LearningDeep Reinforcement Learning for Dynamic Algorithm Selection: A Proof-of-Principle Study on Differential Evolution
Evolutionary algorithms, such as Differential Evolution, excel in solving real-parameter optimization challenges. However, the effectiveness of a single algorithm varies across different problem instances, necessitating …
Deep Reinforcement LearningEvolutionary AlgorithmsSchedulingEvolving machine learning workflows through interactive AutoML
Automatic workflow composition (AWC) is a relevant problem in automated machine learning (AutoML) that allows finding suitable sequences of preprocessing and prediction models together with their optimal hyperparameters.…
AutoMLEvolutionary AlgorithmsICE-SEARCH: A Language Model-Driven Feature Selection Approach
This study unveils the In-Context Evolutionary Search (ICE-SEARCH) method, which is among the first works that melds large language models (LLMs) with evolutionary algorithms for feature selection (FS) tasks and demonstr…
Diabetes PredictionDisease PredictionEvolutionary Algorithmsfeature selection+4Performance Comparison of Surrogate-Assisted Evolutionary Algorithms on Computational Fluid Dynamics Problems
Surrogate-assisted evolutionary algorithms (SAEAs) are recently among the most widely studied methods for their capability to solve expensive real-world optimization problems. However, the development of new methods and …
BenchmarkingEvolutionary AlgorithmsAn Effective Networks Intrusion Detection Approach Based on Hybrid Harris Hawks and Multi-Layer Perceptron
This paper proposes an Intrusion Detection System (IDS) employing the Harris Hawks Optimization algorithm (HHO) to optimize Multilayer Perceptron learning by optimizing bias and weight parameters. HHO-MLP aims to select …
Evolutionary AlgorithmsIntrusion DetectionSensitivitySpecificitySONATA: Self-adaptive Evolutionary Framework for Hardware-aware Neural Architecture Search
Recent advancements in Artificial Intelligence (AI), driven by Neural Networks (NN), demand innovative neural architecture designs, particularly within the constrained environments of Internet of Things (IoT) systems, to…
Evolutionary AlgorithmsHardware Aware Neural Architecture SearchNeural Architecture SearchCompact NSGA-II for Multi-objective Feature Selection
Feature selection is an expensive challenging task in machine learning and data mining aimed at removing irrelevant and redundant features. This contributes to an improvement in classification accuracy, as well as the bu…
Evolutionary Algorithmsfeature selectionEvolutionary Reinforcement Learning: A Systematic Review and Future Directions
In response to the limitations of reinforcement learning and evolutionary algorithms (EAs) in complex problem-solving, Evolutionary Reinforcement Learning (EvoRL) has emerged as a synergistic solution. EvoRL integrates E…
Adversarial RobustnessEvolutionary AlgorithmsFairnessreinforcement-learning+1Is the System Message Really Important to Jailbreaks in Large Language Models?
The rapid evolution of Large Language Models (LLMs) has rendered them indispensable in modern society. While security measures are typically to align LLMs with human values prior to release, recent studies have unveiled …
Evolutionary AlgorithmsLearning Discretized Bayesian Networks with GOMEA
Bayesian networks model relationships between random variables under uncertainty and can be used to predict the likelihood of events and outcomes while incorporating observed evidence. From an eXplainable AI (XAI) perspe…
Evolutionary AlgorithmsA Systematic Evaluation of Evolving Highly Nonlinear Boolean Functions in Odd Sizes
Boolean functions are mathematical objects used in diverse applications. Different applications also have different requirements, making the research on Boolean functions very active. In the last 30 years, evolutionary a…
Evolutionary AlgorithmsSAIS: A Novel Bio-Inspired Artificial Immune System Based on Symbiotic Paradigm
We propose a novel type of Artificial Immune System (AIS): Symbiotic Artificial Immune Systems (SAIS), drawing inspiration from symbiotic relationships in biology. SAIS parallels the three key stages (i.e., mutualism, co…
DiversityEvolutionary AlgorithmsCan Tree Based Approaches Surpass Deep Learning in Anomaly Detection? A Benchmarking Study
Detection of anomalous situations for complex mission-critical systems holds paramount importance when their service continuity needs to be ensured. A major challenge in detecting anomalies from the operational data aris…
Anomaly DetectionBenchmarkingDeep LearningEvolutionary Algorithms+1Evolution and Efficiency in Neural Architecture Search: Bridging the Gap Between Expert Design and Automated Optimization
The paper provides a comprehensive overview of Neural Architecture Search (NAS), emphasizing its evolution from manual design to automated, computationally-driven approaches. It covers the inception and growth of NAS, hi…
Computational EfficiencyEvolutionary AlgorithmsNeural Architecture Search