Aug 8, 2023 � This paper proposes a generic asynchronous evaluation strategy (AES) that is then adapted to work with ENAS. AES increases throughput by maintaining a queue of�...
This paper proposes an asynchronous evaluation strategy called AES that is designed to take full advantage of the available computational resources.
Jan 1, 2024 � Evolution can generate DNNs with diverse topologies and achieve state-of-the-art performance on large-scale visual domains (Real et al., 2019) .
A generic asynchronous evaluation strategy (AES) is proposed that is a promising method for parallelizing the evolution of complex systems with long and�...
Artificial neural networks (ANNs) are versatile tools capable of learning without prior knowledge. This study aims to evaluate whether ANN can calculate minute�...
The concept of decentralised evolutionary computation realised as evolutionary multi-agent system (EMAS) is described in the paper. Also agent- based�...
Asynchronous evolution of deep neural network architectures. https://doi.org/10.1016/j.asoc.2023.111209 �. Journal: Applied Soft Computing, 2024, p. 111209.
evolve also other parameters of learning speed up the evolution - asynchronous evolution, surrogate modeling. Page 42. Deep Networks and RBF Networks.
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Abstract: Due to many successful practical applications, deep neural networks and convolutional networks have be- come the state-of-art machine learning�...
The technology disclosed proposes a novel asynchronous evaluation strategy (AES) that increases throughput of evolutionary algorithms by continuously�...