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cs.LG2026
Can Local Learning Match Self-Supervised Backpropagation?
Wu S. Zihan, Ariane Delrocq, Wulfram Gerstner +1
While end-to-end self-supervised learning with backpropagation (global BP-SSL) has become central for training modern AI systems, theories of local self-supervised learning (local-…
cs.LG2026
Self-supervised local learning rules learn the hidden hierarchical structure of high-dimensional data
Ariane Delrocq, Wu S. Zihan, Guillaume Bellec +1
The brain learns abstract representations of high-dimensional sensory input, but the plasticity rules that enable such learning are unknown. We study biologically plausible algorit…
cs.LG2026
Flat Channels to Infinity in Neural Loss Landscapes
Flavio Martinelli, Alexander Van Meegen, Berfin ÅimÅek +2
The loss landscapes of neural networks contain minima and saddle points that may be connected in flat regions or appear in isolation. We identify and characterize a special structu…