Noam Razin

Computer Science PhD Candidate

Tel Aviv University

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

🗞 News

Jun 23: Interning this summer at  Apple Machine Learning Research.

Mar 23: New paper studies what makes data suitable for locally connected neural networks through tools from quantum physics.
Nov 22: New paper quantifies the ability of graph neural networks to model interactions between vertices. Our theory leads to a promising and simple edge sparsification algorithm.
May 22: Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks accepted to ICML 2022.
📝 Check out this blog post for an overview.
Mar 22: Honored to receive the  2022 Apple Scholars in AI/ML PhD fellowship.
Oct 21: Honored to receive the Tel Aviv University Center for AI & Data Science excellence fellowship.
May 21: Implicit Regularization in Tensor Factorization accepted to ICML 2021.
📝 Check out this blog post for an overview.
Sep 20: Implicit Regularization in Deep Learning May Not Be Explainable by Norms accepted to NeurIPS 2020.
📝 Check out this blog post for an overview.

📄 Publications

* denotes equal contribution.

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

arXiv preprint arXiv:2303.11249, 2023

PDF

On the Ability of Graph Neural Networks to Model Interactions Between Vertices

Noam Razin, Tom Verbin, Nadav Cohen

arXiv preprint arXiv:2211.16494, 2022

PDF Code Poster Video

Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks

Noam Razin, Asaf Maman, Nadav Cohen

International Conference on Machine Learning (ICML), 2022

PDF Code Poster Video Blog

Implicit Regularization in Tensor Factorization

Noam Razin*, Asaf Maman*, Nadav Cohen

International Conference on Machine Learning (ICML), 2021

PDF Code Poster Video Blog

Implicit Regularization in Deep Learning May Not Be Explainable by Norms

Noam Razin, Nadav Cohen

Advances in Neural Information Processing Systems (NeurIPS), 2020

PDF Code Poster Blog

RecoBERT: A Catalog Language Model for Text-Based Recommendations

Itzik Malkiel, Oren Barkan, Avi Caciularu, Noam Razin, Ori Katz, Noam Koenigstein

Findings of the Association for Computational Linguistics: EMNLP, 2020

PDF

Scalable Attentive Sentence-Pair Modeling via Distilled Sentence Embedding

Oren Barkan*, Noam Razin*, Itzik Malkiel, Ori Katz, Avi Caciularu, Noam Koenigstein

AAAI Conference on Artificial Intelligence (AAAI), 2020

PDF Code Poster

💬 Selected Talks

On the Ability of Graph Neural Networks to Model Interactions Between Vertices
Learning on Graphs and Geometry Reading Group, January 2023
Video Slides
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
Video Slides
Generalization in Deep Learning Through the Lens of Implicit Rank Lowering
MPI MiS + UCLA Math Machine Learning Seminar, May 2022
Slides
Implicit Regularization in Tensor Factorization
The Hebrew University Machine Learning Club, Jerusalem, Israel, June 2021
Video Slides
Implicit Regularization in Deep Learning May Not Be Explainable by Norms
Tel Aviv University Machine Learning Seminar, Tel Aviv, Israel, May 2020
Slides

📝 Blog Posts

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

👨‍🏫 Teaching

Teaching Assistant for Foundations of Deep Learning (course #0368-3080), Tel Aviv University, 2021 to present