I’m a PhD candidate in the School of Computer Science at Tel Aviv University, fortunate to be advised by Nadav Cohen.
My research interests broadly include the theoretical foundations and applications of machine learning. More specifically, I focus on mathematically analyzing aspects of deep learning (such as expressiveness, optimization, and generalization), with the goal of establishing theoretically backed practices.
My research is generously supported by the Apple Scholars in AI/ML and the Tel Aviv University Center for AI & Data Science PhD fellowships.
Email: noamrazin (at) mail.tau.ac.il
* denotes equal contribution.
Generalization in Deep Learning Through the Lens of Implicit Rank Lowering
ICTP Youth in High-Dimensions: Recent Progress in Machine Learning, High-Dimensional Statistics and Inference, June 2022
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Generalization in Deep Learning Through the Lens of Implicit Rank Lowering
MPI MiS + UCLA Math Machine Learning Seminar, May 2022
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Implicit Regularization in Tensor Factorization
The Hebrew University Machine Learning Club, Jerusalem, Israel, June 2021
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Implicit Regularization in Deep Learning May Not Be Explainable by Norms
Tel Aviv University Machine Learning Seminar, Tel Aviv, Israel, May 2020
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Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Networks, Off the Convex Path, July 22
Implicit Regularization in Tensor Factorization: Can Tensor Rank Shed Light on Generalization in Deep Learning?, Off the Convex Path, July 21
Can Implicit Regularization in Deep Learning Be Explained by Norms? (by Nadav Cohen), Off the Convex Path, November 20