Abstract: Differential Evolution (DE) algorithm, as a state-of-the-art population-based stochastic optimizer for continuous non-convex search spaces, can adaptively balance exploration and ...

ABSTRACT: Surrogate-assisted evolutionary algorithms are widely used to solve expensive optimization problems due to their high search efficiency. However, a single model struggles to fit various ...

When tools like ChatGPT first launched, they weren’t even connected to the internet. No real-time knowledge, no live queries, just pretrained data with a cutoff point. Two years later, Perplexity, a ...

Abstract: Differential evolution exhibits strong performance in real parameter single objective optimization. Ensemble of similar differential evolution algorithms has been proposed in literature.

ABSTRACT: Mathematical optimization is a fundamental aspect of machine learning (ML). An ML task can be conceptualized as optimizing a specific objective using the training dataset to discern patterns ...

An international team led by the Clínic-IDIBAPS-UB along with the Institute of Cancer Research, London, has developed a new method based on DNA methylation to decipher the origin and evolution of ...