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Accelerating Surrogate Assisted Evolutionary Algorithms Via Explainable Machine Learning
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Modified Distance Calculation in Generational Distance and Inverted Generational Distance
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A novel explainable machine learning approach for EEG-based brain-computer interface systems
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A peek into the black box: exploring classifiers by randomization
inferredcites →https://doi.org/10.1007/s40747-021-00362-5openalex-extracted
Adaptive dropout for high-dimensional expensive multiobjective optimization
inferredcites →https://doi.org/10.1007/s40747-022-00650-8openalex-extracted
Multi-objective multi-criteria evolutionary algorithm for multi-objective multi-task optimization
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A surface parametric control and global optimization method for axial flow compressor blades
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SMS-EMOA: Multiobjective selection based on dominated hypervolume
inferredcites →https://doi.org/10.1016/j.eswa.2020.114104openalex-extracted
Shapley-Lorenz eXplainable Artificial Intelligence
inferredcites →https://doi.org/10.1016/j.swevo.2011.05.001openalex-extracted
Surrogate-assisted evolutionary computation: Recent advances and future challenges
inferredcites →https://doi.org/10.1016/j.swevo.2023.101323openalex-extracted
A pairwise comparison based surrogate-assisted evolutionary algorithm for expensive multi-objective optimization
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The Lorenz Zonoid of a Multivariate Distribution
inferredcites →https://doi.org/10.1088/1742-6596/1288/1/012057openalex-extracted
Survey on Multi-Objective Evolutionary Algorithms
inferredcites →https://doi.org/10.1109/apcap47827.2019.9472059openalex-extracted
Compact Circularly-Polarized Microstrip Antenna for Hand-Held RFID Reader
inferredcites →https://doi.org/10.1109/cec.2002.1007032openalex-extracted
Scalable multi-objective optimization test problems
inferredcites →https://doi.org/10.1109/cec.2015.7257247openalex-extracted
A classification and Pareto domination based multiobjective evolutionary algorithm
inferredcites →https://doi.org/10.1109/mci.2017.2742868openalex-extracted
PlatEMO: A MATLAB Platform for Evolutionary Multi-Objective Optimization [Educational Forum]
inferredcites →https://doi.org/10.1109/tcyb.2018.2794503openalex-extracted
Heterogeneous Ensemble-Based Infill Criterion for Evolutionary Multiobjective Optimization of Expensive Problems
inferredcites →https://doi.org/10.1109/tevc.2003.810761openalex-extracted
The balance between proximity and diversity in multiobjective evolutionary algorithms
inferredcites →https://doi.org/10.1109/tevc.2005.851274openalex-extracted
ParEGO: a hybrid algorithm with on-line landscape approximation for expensive multiobjective optimization problems
inferredcites →https://doi.org/10.1109/tevc.2009.2027359openalex-extracted
Generalizing Surrogate-Assisted Evolutionary Computation
inferredcites →https://doi.org/10.1109/tevc.2009.2033671openalex-extracted
Expensive Multiobjective Optimization by MOEA/D With Gaussian Process Model
inferredcites →https://doi.org/10.1109/tevc.2013.2281534openalex-extracted
An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point Based Nondominated Sorting Approach, Part II: Handling Constraints and Extending to an Adaptive Approach
inferredcites →https://doi.org/10.1109/tevc.2016.2622301openalex-extracted
A Surrogate-Assisted Reference Vector Guided Evolutionary Algorithm for Computationally Expensive Many-Objective Optimization
inferredcites →https://doi.org/10.1109/tevc.2018.2802784openalex-extracted
A Classification-Based Surrogate-Assisted Evolutionary Algorithm for Expensive Many-Objective Optimization
inferredcites →https://doi.org/10.1109/tevc.2022.3152582openalex-extracted
Expensive Multiobjective Optimization by Relation Learning and Prediction
inferredcites →https://doi.org/10.1109/tevc.2022.3159000openalex-extracted
Multiple Classifiers-Assisted Evolutionary Algorithm Based on Decomposition for High-Dimensional Multiobjective Problems
inferredcites →https://doi.org/10.1109/tevc.2023.3234269openalex-extracted
Interactive Evolutionary Multiobjective Optimization via Learning to Rank
inferredcites →https://doi.org/10.1109/tsmc.2020.3044418openalex-extracted
Evolutionary Optimization of High-Dimensional Multiobjective and Many-Objective Expensive Problems Assisted by a Dropout Neural Network
inferredcites →https://doi.org/10.1145/3236009openalex-extracted
A Survey of Methods for Explaining Black Box Models
inferredcites →https://doi.org/10.1145/3468264.3468555openalex-extracted
Multi-objectivizing software configuration tuning
inferredcites →https://doi.org/10.1145/3470971openalex-extracted
Evolutionary Large-Scale Multi-Objective Optimization: A Survey
inferredcites →https://doi.org/10.1145/3520304.3529032openalex-extracted
Evolving parsimonious circuits through shapley value-based genetic programming
inferredcites →https://doi.org/10.1145/3583133.3590619openalex-extracted
Explaining Memristive Reservoir Computing Through Evolving Feature Attribution
inferredcites →https://doi.org/10.18653/v1/n16-3020openalex-extracted
“Why Should I Trust You?”: Explaining the Predictions of Any Classifier
inferredcites →https://doi.org/10.2307/254267openalex-extracted
Nonlinear Multiobjective Optimization
inferredcites →https://doi.org/10.2514/6.1996-4161openalex-extracted
Conceptual design of a family of products through the use of the Robust Concept Extrapolation Method
inferredcites →https://doi.org/10.3929/ethz-a-004288833openalex-extracted
An evolutionary algorithm for multiobjective optimization: the strength Pareto approach
inferredcites →https://doi.org/10.4230/oasics.dx.2024.27openalex-extracted
On a Method to Measure Supervised Multiclass Model’s Interpretability: Application to Degradation Diagnosis (Short Paper)
inferredcites →https://doi.org/10.48550/arxiv.1702.08608openalex-extracted
Towards A Rigorous Science of Interpretable Machine Learning
inferredcites →https://doi.org/10.48550/arxiv.1705.07874openalex-extracted
A Unified Approach to Interpreting Model Predictions
inferredcites →https://doi.org/10.48550/arxiv.1810.03522openalex-extracted
NSGA-Net: Neural Architecture Search using Multi-Objective Genetic Algorithm
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Fooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation Methods
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Have We Learned to Explain?: How Interpretability Methods Can Learn to Encode Predictions in their Interpretations
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