To address this gap, we study deterministic/stochastic versions of SAM with practical configurations (i.e., constant

One challenge of continual learning is "catastrophic forgetting" [Had+20; VT19; Kem+18]: A model However, if contexts similar to A arise repeatedly, this may be undesirable.. In machine learning, many data sets display cyclic or periodic patterns.

Sharpness-A ware Minimization (SAM) is a recently proposed gradient-based optimizer (Foret et al., ICLR 2021) that greatly improves the prediction performance of deep neural networks.

We provide the detailed of the PQ retrieval performance trends of Glint360K trained using the CosFace loss in Tab. 1.

Transformers have achieved great success in machine learning applications.

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Model-free reinforcement learning aims to offer off-the-shelf solutions for controlling dynamical systems without requiring models of the system dynamics.