2 papers
cs.LG2026
SingularClip: Preventing Spectral Collapse to Maintain Plasticity in Continual and Reinforcement Learning
Tyler Kastner, Nimrod De La Vega, Amir-massoud Farahmand
Neural networks trained on nonstationary tasks frequently lose the ability to fit new targets, a phenomenon referred to as loss of plasticity. We identify a novel source of plastic…
cs.LG2023
What Makes Data Suitable for a Locally Connected Neural Network? A Necessary and Sufficient Condition Based on Quantum Entanglement
Yotam Alexander, Nimrod De La Vega, Noam Razin +1
The question of what makes a data distribution suitable for deep learning is a fundamental open problem. Focusing on locally connected neural networks (a prevalent family of archit…