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Maxim Bazhenov

2 accepted papers

2025

When to Learn and When to Stop: Quitting at the Optimal Time (Student Abstract)

AAAI 2025technical

Artificial neural networks (ANNs) struggle with continual learning, sacrificing performance on previously learned tasks to acquire new task knowledge. Here we propose a new approach allowing to mitigate catastrophic forgetting during continuous task learning. Typically a new task is trained until it…

Cited by 0SourcePDFScholar
2020

Biologically inspired sleep algorithm for increased generalization and adversarial robustness in deep neural networks

ICLR 2020poster

Current artificial neural networks (ANNs) can perform and excel at a variety of tasks ranging from image classification to spam detection through training on large datasets of labeled data. While the trained network may perform well on similar testing data, inputs that differ even slightly from the…

Cited by 24SourceScholar