Bayesian Optimization Meets Networked Data
A new study introduces a framework for applying Bayesian optimization—a powerful machine learning technique for finding the maximum of unknown functions—to problems defined on networks. This approach is particularly relevant for complex systems where data points are not independent but connected in a graph structure, a common scenario in social networks, biological interactions, and certain AI architectures.
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