Alexander, Yotam

5 publications

NeurIPS 2025 Do Neural Networks Need Gradient Descent to Generalize? a Theoretical Study Yotam Alexander, Yonatan Slutzky, Yuval Ran-Milo, Nadav Cohen

NeurIPS 2025 Revisiting Glorot Initialization for Long-Range Linear Recurrences Noga Bar, Mariia Seleznova, Yotam Alexander, Gitta Kutyniok, Raja Giryes

NeurIPS 2025 The Implicit Bias of Structured State Space Models Can Be Poisoned with Clean Labels Yonatan Slutzky, Yotam Alexander, Noam Razin, Nadav Cohen

ICML 2024 Implicit Bias of Policy Gradient in Linear Quadratic Control: Extrapolation to Unseen Initial States Noam Razin, Yotam Alexander, Edo Cohen-Karlik, Raja Giryes, Amir Globerson, Nadav Cohen

NeurIPS 2023 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, Nadav Cohen