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A distributional simplicity bias in the learning dynamics of transformers

Neural Information Processing Systems

The remarkable capability of over-parameterised neural networks to generalise effectively has been explained by invoking a "simplicity bias": neural networks prevent overfitting by initially learning simple classifiers before progressing to


Parameter Symmetry and Noise Equilibrium of Stochastic Gradient Descent Liu Ziyin Massachusetts Institute of Technology, NTT Research

Neural Information Processing Systems

Symmetries are prevalent in deep learning and can significantly influence the learning dynamics of neural networks. In this paper, we examine how exponential symmetries - a broad subclass of continuous symmetries present in the model architecture or loss function - interplay with stochastic gradient descent (SGD). We first prove that gradient noise creates a systematic motion (a "Noether flow") of the parameters θ along the degenerate direction to a unique initialization-independent fixed point θ



Ancient bone may prove legendary war elephant crossing of Alps

BBC News

An elephant foot bone found by archaeologists digging in southern Spain may be evidence that a troop of war elephants stomped through ancient Europe. It would be the first concrete proof of the legendary Carthaginian General Hannibal's troop of battle elephants, according to academics. Drawings of Hannibal's war against the Romans had long suggested that the beasts were used in fighting, but no hard evidence backed up the theories. Now the creatures' skeletal remains appear to have been found in an Iron Age dig near Cordoba. Beyond ivory, the discovery of elephant remains in European archaeological contexts is exceptionally rare, says the team of scientists in a paper published in Journal of Archaeological Science: Reports.