Authors

Joel Zylberberg

Publications 2

Preprint Open access

Signal-Noise Factorization Isolates Nuisance Variation into Removable Subspaces

Sakin Kirti, Joel Zylberberg · 2026

Recent theoretical work identified fundamental properties of representation geometry that shape inference ability of deep neural networks. These include signal-noise factorization (SNF), the ability to segregate signal from noise, and signal-signal factorization (SSF), the ability to segregate task-specific and task-ir …

Preprint Open access

Increasing Width Allows Greedy Layer-wise Training to Rival End-to-End Backpropagation in Self-Supervised Learning

Syon Mansur, Joel Zylberberg · 2026

End-to-end backpropagation has been the dominant mode of training in deep learning, allowing for the coordination of parameter updates across layers of a neural network. Prior studies have explored alternative -- and, in some cases, simpler -- training mechanisms, showing that they can sometimes achieve performance sim …

Co-authors

Syon Mansur Sakin Kirti