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cs.LG2026
The Effect of Mini-Batch Noise on the Implicit Bias of Adam
Matias D. Cattaneo, Boris Shigida
With limited high-quality data and growing compute, multi-epoch training is gaining back its importance across sub-areas of deep learning. Adam(W), versions of which are go-to opti…
cs.LG2025
Modified Loss of Momentum Gradient Descent: Fine-Grained Analysis
Matias D. Cattaneo, Boris Shigida
We analyze gradient descent with Polyak (1964) heavy-ball momentum (HB) whose fixed momentum hyperparameter provides exponential decay of memory. Building on Kovachki…
cs.LG2025
How Memory in Optimization Algorithms Implicitly Modifies the Loss
Matias D. Cattaneo, Boris Shigida
In modern optimization methods used in deep learning, each update depends on the history of previous iterations, often referred to as memory, and this dependence decays fast as the…