Sparse regression with highly correlated predictors. - Behrooz Ghorbani; Özgür Yilmaz (CoRR, 2015)

An Instability in Variational Inference for Topic Models. - Behrooz Ghorbani; Hamid Javadi; Andrea Montanari (ICML, 2019)

An Investigation into Neural Net Optimization via Hessian Eigenvalue Density. - Behrooz Ghorbani; Shankar Krishnan; Ying Xiao (ICML, 2019)

Limitations of Lazy Training of Two-layers Neural Network. - Behrooz Ghorbani; Song Mei; Theodor Misiakiewicz; Andrea Montanari (NeurIPS, 2019)

Linearized two-layers neural networks in high dimension. - Behrooz Ghorbani; Song Mei; Theodor Misiakiewicz; Andrea Montanari (CoRR, 2019)

Limitations of Lazy Training of Two-layers Neural Networks. - Behrooz Ghorbani; Song Mei; Theodor Misiakiewicz; Andrea Montanari (CoRR, 2019)

When Do Neural Networks Outperform Kernel Methods? - Behrooz Ghorbani; Song Mei; Theodor Misiakiewicz; Andrea Montanari (NeurIPS, 2020)

A Loss Curvature Perspective on Training Instability in Deep Learning. - Justin Gilmer; Behrooz Ghorbani; Ankush Garg; Sneha Kudugunta; Behnam Neyshabur; David Cardoze; George E. Dahl; Zachary Nado; Orhan Firat (CoRR, 2021)

Scaling Laws for Neural Machine Translation. - Behrooz Ghorbani; Orhan Firat; Markus Freitag; Ankur Bapna; Maxim Krikun; Xavier Garcia; Ciprian Chelba; Colin Cherry (ICLR, 2022)

A Loss Curvature Perspective on Training Instabilities of Deep Learning Models. - Justin Gilmer; Behrooz Ghorbani; Ankush Garg; Sneha Kudugunta; Behnam Neyshabur; David Cardoze; George Edward Dahl; Zachary Nado; Orhan Firat (ICLR, 2022)

Data Scaling Laws in NMT: The Effect of Noise and Architecture. - Yamini Bansal; Behrooz Ghorbani; Ankush Garg; Biao Zhang 006; Colin Cherry; Behnam Neyshabur; Orhan Firat (ICML, 2022)

Examining Scaling and Transfer of Language Model Architectures for Machine Translation. - Biao Zhang 006; Behrooz Ghorbani; Ankur Bapna; Yong Cheng; Xavier Garcia; Jonathan Shen; Orhan Firat (ICML, 2022)

Do Current Multi-Task Optimization Methods in Deep Learning Even Help? - Derrick Xin; Behrooz Ghorbani; Justin Gilmer; Ankush Garg; Orhan Firat (NeurIPS, 2022)

Data Scaling Laws in NMT: The Effect of Noise and Architecture. - Yamini Bansal; Behrooz Ghorbani; Ankush Garg; Biao Zhang 006; Maxim Krikun; Colin Cherry; Behnam Neyshabur; Orhan Firat (CoRR, 2022)

Adaptive Gradient Methods at the Edge of Stability. - Jeremy Cohen 001; Behrooz Ghorbani; Shankar Krishnan; Naman Agarwal; Sourabh Medapati; Michal Badura; Daniel Suo; David Cardoze; Zachary Nado; George E. Dahl; Justin Gilmer (CoRR, 2022)

Epsilon Sampling Rocks: Investigating Sampling Strategies for Minimum Bayes Risk Decoding for Machine Translation. - Markus Freitag; Behrooz Ghorbani; Patrick Fernandes (EMNLP (Findings), 2023)

Scaling Laws for Multilingual Neural Machine Translation. - Patrick Fernandes; Behrooz Ghorbani; Xavier Garcia; Markus Freitag; Orhan Firat (ICML, 2023)

Binarized Neural Machine Translation. - Yichi Zhang 006; Ankush Garg; Yuan Cao; Lukasz Lew; Behrooz Ghorbani; Zhiru Zhang; Orhan Firat (NeurIPS, 2023)

Order Matters in the Presence of Dataset Imbalance for Multilingual Learning. - Dami Choi; Derrick Xin; Hamid Dadkhahi; Justin Gilmer; Ankush Garg; Orhan Firat; Chih-Kuan Yeh; Andrew M. Dai; Behrooz Ghorbani (NeurIPS, 2023)

GPT-4o System Card. - Aaron Hurst; Adam Lerer; Adam P. Goucher; Adam Perelman; Aditya Ramesh; Aidan Clark; AJ Ostrow; Akila Welihinda; Alan Hayes; Alec Radford; Aleksander Madry; Alex Baker-Whitcomb; et al. (CoRR, 2024)

OpenAI o1 System Card. - Aaron Jaech; Adam Kalai; Adam Lerer; Adam Richardson; Ahmed El-Kishky; Aiden Low; Alec Helyar; Aleksander Madry; Alex Beutel; Alex Carney; Alex Iftimie; Alex Karpenko; et al. (CoRR, 2024)