We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors ...

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.

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

Richard Feynman described a decision-making problem and its solution in handwritten notes, but the meaning of the notes has been a mystery for almost 50 y. We decipher the problem and solution from ...

Accurate solar irradiance forecasting is increasingly crucial for managing solar energy systems effectively, as their power output is directly dependent on solar irradiance (SI). Several models in the ...

Decisions based on evidence accumulated over time require rules governing when to end the accumulation process and commit to a choice. These rules control inherent trade-offs between decision speed ...

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 ...

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 ...

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 ...

Customer stories Events & webinars Ebooks & reports Business insights GitHub Skills ...

Customer stories Events & webinars Ebooks & reports Business insights GitHub Skills ...

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