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cs.LG2025
Efficient and Flexible Neural Network Training through Layer-wise Feedback Propagation
Leander Weber, Jim Berend, Moritz Weckbecker +4
Gradient-based optimization has been a cornerstone of machine learning that enabled the vast advances of Artificial Intelligence (AI) development over the past decades. However, th…
cs.LG2025
Relevance-driven Input Dropout: an Explanation-guided Regularization Technique
Shreyas Gururaj, Lars Grüne, Wojciech Samek +2
Overfitting is a well-known issue extending even to state-of-the-art (SOTA) Machine Learning (ML) models, resulting in reduced generalization, and a significant train-test performa…