Machine Learning Robustness: A Primer

arXiv:2404.00897v1 Announce Type: new
Abstract: This chapter explores the foundational concept of robustness in Machine Learning (ML) and its integral role in establishing trustworthiness in Artificial Intelligence (AI) systems. The discussion begins with a detailed definition of robustness, portraying it as the ability of ML models to maintain stable performance across varied and unexpected environmental conditions. ML robustness is dissected through several lenses: its complementarity with generalizability; its status as a requirement for trustworthy AI; its adversarial vs non-adversarial aspects; …

abstract artificial artificial intelligence arxiv concept cs.ai cs.lg cs.se definition environmental foundational integral intelligence machine machine learning ml models performance primer robustness role systems type