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cs.LG2026
On the Stability of the Jacobian Matrix in Deep Neural Networks
Benjamin Dadoun, Soufiane Hayou, Hanan Salam +2
Deep neural networks are known to suffer from exploding or vanishing gradients as depth increases, a phenomenon closely tied to the spectral behavior of the input-output Jacobian.…
cs.LG2024
Finite-Sample Analysis of the Monte Carlo Exploring Starts Algorithm for Reinforcement Learning
Suei-Wen Chen, Keith Ross, Pierre Youssef
Monte Carlo Exploring Starts (MCES), which aims to learn the optimal policy using only sample returns, is a simple and natural algorithm in reinforcement learning which has been sh…
cs.LG2024
How Bad is Training on Synthetic Data? A Statistical Analysis of Language Model Collapse
Mohamed El Amine Seddik, Suei-Wen Chen, Soufiane Hayou +2
The phenomenon of model collapse, introduced in (Shumailov et al., 2023), refers to the deterioration in performance that occurs when new models are trained on synthetic data gener…