A Machine Learning Based Explainability Framework for Interpreting Swarm Intelligence
Fuente:
arXiv
Saved in:
| Main Authors: | Gupta, Nitin, Dutta, Bapi, Yadav, Anupam |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
An Explainable Reconfiguration-Based Optimization Algorithm for Industrial and Reliability-Redundancy Allocation Problems
by: Chauhan, Dikshit, et al.
Published: (2025)
by: Chauhan, Dikshit, et al.
Published: (2025)
AdaSwarm: Augmenting Gradient-Based optimizers in Deep Learning with Swarm Intelligence
by: Mohapatra, Rohan, et al.
Published: (2020)
by: Mohapatra, Rohan, et al.
Published: (2020)
SwarmFusion: Revolutionizing Disaster Response with Swarm Intelligence and Deep Learning
by: Lankipalle, Vasavi
Published: (2025)
by: Lankipalle, Vasavi
Published: (2025)
Polyra Swarms: A Shape-Based Approach to Machine Learning
by: Klüttermann, Simon, et al.
Published: (2025)
by: Klüttermann, Simon, et al.
Published: (2025)
A White-Box SVM Framework and its Swarm-Based Optimization for Supervision of Toothed Milling Cutter through Characterization of Spindle Vibrations
by: Deo, Tejas Y., et al.
Published: (2021)
by: Deo, Tejas Y., et al.
Published: (2021)
A Critical Analysis of the Theoretical Framework of the Extreme Learning Machine
by: Perfilievaa, Irina, et al.
Published: (2024)
by: Perfilievaa, Irina, et al.
Published: (2024)
Genetic Programming for Explainable Manifold Learning
by: Cravens, Ben, et al.
Published: (2024)
by: Cravens, Ben, et al.
Published: (2024)
LightCPPgen: An Explainable Machine Learning Pipeline for Rational Design of Cell Penetrating Peptides
by: Maroni, Gabriele, et al.
Published: (2024)
by: Maroni, Gabriele, et al.
Published: (2024)
Structuring Multiple Simple Cycle Reservoirs with Particle Swarm Optimization
by: Li, Ziqiang, et al.
Published: (2025)
by: Li, Ziqiang, et al.
Published: (2025)
Towards Precision in Bolted Joint Design: A Preliminary Machine Learning-Based Parameter Prediction
by: Boujnah, Ines, et al.
Published: (2024)
by: Boujnah, Ines, et al.
Published: (2024)
A Review of Neuroscience-Inspired Machine Learning
by: Ororbia, Alexander, et al.
Published: (2024)
by: Ororbia, Alexander, et al.
Published: (2024)
DDCL: Deep Dual Competitive Learning: A Differentiable End-to-End Framework for Unsupervised Prototype-Based Representation Learning
by: Cirrincione, Giansalvo
Published: (2026)
by: Cirrincione, Giansalvo
Published: (2026)
Towards Interpretable Deep Local Learning with Successive Gradient Reconciliation
by: Yang, Yibo, et al.
Published: (2024)
by: Yang, Yibo, et al.
Published: (2024)
A Hybrid Swarm Intelligence Approach for Optimizing Multimodal Large Language Models Deployment in Edge-Cloud-based Federated Learning Environments
by: Rjouba, Gaith, et al.
Published: (2025)
by: Rjouba, Gaith, et al.
Published: (2025)
Evolutionary Dynamic Optimization and Machine Learning
by: Boulesnane, Abdennour
Published: (2023)
by: Boulesnane, Abdennour
Published: (2023)
A Machine Learning Approach to Automatic Fall Detection of Soldiers
by: Soares, Leandro, et al.
Published: (2025)
by: Soares, Leandro, et al.
Published: (2025)
Evolutionary Computation and Explainable AI: A Roadmap to Understandable Intelligent Systems
by: Zhou, Ryan, et al.
Published: (2024)
by: Zhou, Ryan, et al.
Published: (2024)
Analysis and Explainability of LLMs Via Evolutionary Methods
by: Gallagher, Shannon K., et al.
Published: (2026)
by: Gallagher, Shannon K., et al.
Published: (2026)
Machine Learning-Based Classification of Jhana Advanced Concentrative Absorption Meditation (ACAM-J) using 7T fMRI
by: Kumar, Puneet, et al.
Published: (2026)
by: Kumar, Puneet, et al.
Published: (2026)
Learning Numeracy: Binary Arithmetic with Neural Turing Machines
by: Castellini, Jacopo
Published: (2019)
by: Castellini, Jacopo
Published: (2019)
Evolutionary Machine Learning meets Self-Supervised Learning: a comprehensive survey
by: Vinhas, Adriano, et al.
Published: (2025)
by: Vinhas, Adriano, et al.
Published: (2025)
Multi-Class Imbalanced Learning with Support Vector Machines via Differential Evolution
by: Zhang, Zhong-Liang, et al.
Published: (2025)
by: Zhang, Zhong-Liang, et al.
Published: (2025)
Rethinking Deep Learning: Non-backpropagation and Non-optimization Machine Learning Approach Using Hebbian Neural Networks
by: Itoh, Kei
Published: (2024)
by: Itoh, Kei
Published: (2024)
A Review of 315 Benchmark and Test Functions for Machine Learning Optimization Algorithms and Metaheuristics with Mathematical and Visual Descriptions
by: Naser, M. Z., et al.
Published: (2024)
by: Naser, M. Z., et al.
Published: (2024)
A General Framework for Interpretable Neural Learning based on Local Information-Theoretic Goal Functions
by: Makkeh, Abdullah, et al.
Published: (2023)
by: Makkeh, Abdullah, et al.
Published: (2023)
StarBASE-GP: Biologically-Guided Automated Machine Learning for Genotype-to-Phenotype Association Analysis
by: Hernandez, Jose Guadalupe, et al.
Published: (2025)
by: Hernandez, Jose Guadalupe, et al.
Published: (2025)
Interpretable Non-linear Survival Analysis with Evolutionary Symbolic Regression
by: Rovito, Luigi, et al.
Published: (2025)
by: Rovito, Luigi, et al.
Published: (2025)
Classifying States of the Hopfield Network with Improved Accuracy, Generalization, and Interpretability
by: McAlister, Hayden, et al.
Published: (2025)
by: McAlister, Hayden, et al.
Published: (2025)
Optimizing Neural Network Performance and Interpretability with Diophantine Equation Encoding
by: Katende, Ronald
Published: (2024)
by: Katende, Ronald
Published: (2024)
Interpretable Solutions for Breast Cancer Diagnosis with Grammatical Evolution and Data Augmentation
by: Hasan, Yumnah, et al.
Published: (2024)
by: Hasan, Yumnah, et al.
Published: (2024)
Generalization-Memorization Machines
by: Wang, Zhen, et al.
Published: (2022)
by: Wang, Zhen, et al.
Published: (2022)
Deep Learning-Based Operators for Evolutionary Algorithms
by: Shem-Tov, Eliad, et al.
Published: (2024)
by: Shem-Tov, Eliad, et al.
Published: (2024)
Lifelong Intelligence Beyond the Edge using Hyperdimensional Computing
by: Yu, Xiaofan, et al.
Published: (2024)
by: Yu, Xiaofan, et al.
Published: (2024)
Why Flow Matching is Particle Swarm Optimization?
by: Ouyang, Kaichen
Published: (2025)
by: Ouyang, Kaichen
Published: (2025)
Effective Predictive Modeling for Emergency Department Visits and Evaluating Exogenous Variables Impact: Using Explainable Meta-learning Gradient Boosting
by: Neshat, Mehdi, et al.
Published: (2024)
by: Neshat, Mehdi, et al.
Published: (2024)
Epidemic Modeling using Hybrid of Time-varying SIRD, Particle Swarm Optimization, and Deep Learning
by: Kumar, Naresh, et al.
Published: (2024)
by: Kumar, Naresh, et al.
Published: (2024)
Fuzzy Clustering to Identify Clusters at Different Levels of Fuzziness: An Evolutionary Multi-Objective Optimization Approach
by: Gupta, Avisek, et al.
Published: (2018)
by: Gupta, Avisek, et al.
Published: (2018)
Projective Kolmogorov Arnold Neural Networks (P-KANs): Entropy-Driven Functional Space Discovery for Interpretable Machine Learning
by: Poole, Alastair, et al.
Published: (2025)
by: Poole, Alastair, et al.
Published: (2025)
Advancing CMA-ES with Learning-Based Cooperative Coevolution for Scalable Optimization
by: Guo, Hongshu, et al.
Published: (2025)
by: Guo, Hongshu, et al.
Published: (2025)
Data-Driven Discovery of Interpretable Kalman Filter Variants through Large Language Models and Genetic Programming
by: Saketos, Vasileios, et al.
Published: (2025)
by: Saketos, Vasileios, et al.
Published: (2025)
Similar Items
-
An Explainable Reconfiguration-Based Optimization Algorithm for Industrial and Reliability-Redundancy Allocation Problems
by: Chauhan, Dikshit, et al.
Published: (2025) -
AdaSwarm: Augmenting Gradient-Based optimizers in Deep Learning with Swarm Intelligence
by: Mohapatra, Rohan, et al.
Published: (2020) -
SwarmFusion: Revolutionizing Disaster Response with Swarm Intelligence and Deep Learning
by: Lankipalle, Vasavi
Published: (2025) -
Polyra Swarms: A Shape-Based Approach to Machine Learning
by: Klüttermann, Simon, et al.
Published: (2025) -
A White-Box SVM Framework and its Swarm-Based Optimization for Supervision of Toothed Milling Cutter through Characterization of Spindle Vibrations
by: Deo, Tejas Y., et al.
Published: (2021)