Brochu, E., Cora, V.M. and de Freitas, N. (2010) A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning.

Reference: Garrido Torres, Jose A.; Lau, Sii Hong; Anchuri, Pranay; Stevens, Jason M.; Tabora, Jose E.; Li, Jun; Borovika, Alina; Adams, Ryan P.; Doyle, Abigail G. "A ...

Here, we benchmark five global optimization methods for three typical nano-optical optimization problems: particle swarm optimization, differential evolution, and Bayesian optimization as well as ...

Probabilistic models, such as hidden Markov models or Bayesian networks, are commonly used to model biological data. Much of their popularity can be attributed to the existence of efficient and robust ...

Abstract: Decomposition has been the mainstream approach in the classic mathematical programming for multi-objective optimization and multi-criterion decision-making. However, it was not properly ...

Abstract: Integrated sensing and communications (ISAC) is a key enabler for next-generation wireless systems, aiming to support both high-throughput communication and ...

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Thanks to their rapid evolution, viral genomes can be analyzed and compared to estimate the dispersal history of the virus responsible for an epidemic, a task known as phylogeographic inference. In ...

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