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06/26/2023
Data-Driven Chance-Constrained Multiple-Choice Knapsack Problem: Model, Algorithms, and Applications
The multiple-choice knapsack problem (MCKP) is a classic NP-hard combina...
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05/24/2023
Prompt Evolution for Generative AI: A Classifier-Guided Approach
Synthesis of digital artifacts conditioned on user prompts has become an...
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04/26/2023
Bayesian Federated Learning: A Survey
Federated learning (FL) demonstrates its advantages in integrating distr...
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12/15/2022
Neuroevolution Surpasses Stochastic Gradient Descent for Physics-Informed Neural Networks
The potential of learned models for fundamental scientific research and ...
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04/14/2021
Multi-Party Dual Learning
The performance of machine learning algorithms heavily relies on the ava...
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12/03/2020
Scalable Transfer Evolutionary Optimization: Coping with Big Task Instances
In today's digital world, we are confronted with an explosion of data an...
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11/03/2018
