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cs.LG2025
A Classical View on Benign Overfitting: The Role of Sample Size
Junhyung Park, Patrick Bloebaum, Shiva Prasad Kasiviswanathan
Benign overfitting is a phenomenon in machine learning where a model perfectly fits (interpolates) the training data, including noisy examples, yet still generalizes well to unseen…
cs.LG2024
Benign Overfitting for Regression with Trained Two-Layer ReLU Networks
Junhyung Park, Patrick Bloebaum, Shiva Prasad Kasiviswanathan
We study the least-square regression problem with a two-layer fully-connected neural network, with ReLU activation function, trained by gradient flow. Our first result is a general…