Hussein Hazimeh

According to our database, Hussein Hazimeh authored at least 18 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

DART: A Principled Approach to Adversarially Robust Unsupervised Domain Adaptation.

Yunjuan Wang, Hussein Hazimeh, Natalia Ponomareva, Alexey Kurakin, Ibrahim Hammoud, Raman Arora

CoRR, 2024

Scaling Laws for Downstream Task Performance of Large Language Models.

Berivan Isik, Natalia Ponomareva, Hussein Hazimeh, Dimitris Paparas, Sergei Vassilvitskii, Sanmi Koyejo

CoRR, 2024

OSSCAR: One-Shot Structured Pruning in Vision and Language Models with Combinatorial Optimization.

Xiang Meng, Shibal Ibrahim, Kayhan Behdin, Hussein Hazimeh, Natalia Ponomareva, Rahul Mazumder

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

L0Learn: A Scalable Package for Sparse Learning using L0 Regularization.

Hussein Hazimeh, Rahul Mazumder, Tim Nonet

J. Mach. Learn. Res., 2023

How to DP-fy ML: A Practical Guide to Machine Learning with Differential Privacy.

Natalia Ponomareva, Hussein Hazimeh, Alex Kurakin, Zheng Xu, Carson Denison, H. Brendan McMahan, Sergei Vassilvitskii, Steve Chien, Abhradeep Guha Thakurta

J. Artif. Intell. Res., 2023

Benchmarking Robustness to Adversarial Image Obfuscations.

Florian Stimberg, Ayan Chakrabarti, Chun-Ta Lu, Hussein Hazimeh, Otilia Stretcu, Wei Qiao, Yintao Liu, Merve Kaya, Cyrus Rashtchian, Ariel Fuxman, Mehmet Tek, Sven Gowal

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

COMET: Learning Cardinality Constrained Mixture of Experts with Trees and Local Search.

Shibal Ibrahim, Wenyu Chen, Hussein Hazimeh, Natalia Ponomareva, Zhe Zhao, Rahul Mazumder

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Fast as CHITA: Neural Network Pruning with Combinatorial Optimization.

Riade Benbaki, Wenyu Chen, Xiang Meng, Hussein Hazimeh, Natalia Ponomareva, Zhe Zhao, Rahul Mazumder

Proceedings of the International Conference on Machine Learning, 2023

Mind the (optimality) Gap: A Gap-Aware Learning Rate Scheduler for Adversarial Nets.

Hussein Hazimeh, Natalia Ponomareva

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Sparse regression at scale: branch-and-bound rooted in first-order optimization.

Hussein Hazimeh, Rahul Mazumder, Ali Saab

Math. Program., 2022

Flexible Modeling and Multitask Learning using Differentiable Tree Ensembles.

Shibal Ibrahim, Hussein Hazimeh, Rahul Mazumder

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

2021

Learning Sparse Classifiers: Continuous and Mixed Integer Optimization Perspectives.

Antoine Dedieu, Hussein Hazimeh, Rahul Mazumder

J. Mach. Learn. Res., 2021

Grouped Variable Selection with Discrete Optimization: Computational and Statistical Perspectives.

Hussein Hazimeh, Rahul Mazumder, Peter Radchenko

CoRR, 2021

DSelect-k: Differentiable Selection in the Mixture of Experts with Applications to Multi-Task Learning.

Hussein Hazimeh, Zhe Zhao, Aakanksha Chowdhery, Maheswaran Sathiamoorthy, Yihua Chen, Rahul Mazumder, Lichan Hong, Ed H. Chi

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Fast Best Subset Selection: Coordinate Descent and Local Combinatorial Optimization Algorithms.

Hussein Hazimeh, Rahul Mazumder

Oper. Res., 2020

The Tree Ensemble Layer: Differentiability meets Conditional Computation.

Hussein Hazimeh, Natalia Ponomareva, Petros Mol, Zhenyu Tan, Rahul Mazumder

Proceedings of the 37th International Conference on Machine Learning, 2020

Learning Hierarchical Interactions at Scale: A Convex Optimization Approach.

Hussein Hazimeh, Rahul Mazumder

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2015

Axiomatic Analysis of Smoothing Methods in Language Models for Pseudo-Relevance Feedback.

Hussein Hazimeh, ChengXiang Zhai

Proceedings of the 2015 International Conference on The Theory of Information Retrieval, 2015