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 ...

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.

In recent years, the frequency of weather-related natural disasters—cyclones, torrential rains, floods—has increased as a consequence of global warming. These disasters cause billions of dollars in ...

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 ...

Find out more about undergraduate study at the School of Electronic Engineering and Computer Science.

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 ...

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 ...

This course is designed for Ph.D. students whose primary field of study is machine learning, or who intend to make machine learning methodological research a main focus of their thesis. It will give ...

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 ...

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