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arXiv Machine Learning By Konstantinos Zacharopoulos, Alexandra Bekou, Jose M Serradell, Foteini Paraskevopoulou, Apostolos Fournaris, Ioannis Arapakis, Oscar Lao

TRON: Transferring Naturally Evolved Network Architectures into Neuroevolution

Read the original on arXiv Machine Learning →

TRON (TRansfer Of Natural networks) is a neuroevolution framework that uses experimentally characterized protein‑protein interaction (PPI) networks as architectural priors instead of random topologies. By combining classical evolutionary operators with neuroevolution techniques such as speciation and species quarantine, TRON improves the preservation of functional organization during mutation and recombination. Evaluations on six benchmark datasets show that TRON achieves the best predictive performance on all classification tasks and most regression tasks, with lower variability across runs, indicating greater robustness and convergence stability at the cost of higher computational effort.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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