no code implementations • 23 Jan 2024 • Elizaveta Demyanenko, Christoph Feinauer, Enrico M. Malatesta, Luca Saglietti
Recent works demonstrated the existence of a double-descent phenomenon for the generalization error of neural networks, where highly overparameterized models escape overfitting and achieve good test performance, at odds with the standard bias-variance trade-off described by statistical learning theory.
1 code implementation • ICLR 2021 • Fabrizio Pittorino, Carlo Lucibello, Christoph Feinauer, Gabriele Perugini, Carlo Baldassi, Elizaveta Demyanenko, Riccardo Zecchina
The properties of flat minima in the empirical risk landscape of neural networks have been debated for some time.