Stretching de Bruijn sequences. - Abbas Alhakim; Maher Nouiehed (Des. Codes Cryptogr., 2017)

A conjecture on the Feldman bandit problem. - Maher Nouiehed; Sheldon M. Ross (J. Appl. Probab., 2018)

Solving a Class of Non-Convex Min-Max Games Using Iterative First Order Methods. - Maher Nouiehed; Maziar Sanjabi; Tianjian Huang; Jason D. Lee; Meisam Razaviyayn (NeurIPS, 2019)

Rényi Fair Inference. - Sina Baharlouei; Maher Nouiehed; Meisam Razaviyayn (CoRR, 2019)

On the pervasiveness of difference-convexity in optimization and statistics. - Maher Nouiehed; Jong-Shi Pang; Meisam Razaviyayn (Math. Program., 2019)

Correction to: On the pervasiveness of difference-convexity in optimization and statistics. - Maher Nouiehed; Jong-Shi Pang; Meisam Razaviyayn (Math. Program., 2019)

Rényi Fair Inference. - Sina Baharlouei; Maher Nouiehed; Ahmad Beirami; Meisam Razaviyayn (ICLR, 2020)

Non-convex Min-Max Optimization: Applications, Challenges, and Recent Theoretical Advances. - Meisam Razaviyayn; Tianjian Huang; Songtao Lu; Maher Nouiehed; Maziar Sanjabi; Mingyi Hong 001 (CoRR, 2020)

SALR: Sharpness-aware Learning Rates for Improved Generalization. - Xubo Yue; Maher Nouiehed; Raed Al Kontar (CoRR, 2020)

A Trust Region Method for Finding Second-Order Stationarity in Linearly Constrained Nonconvex Optimization. - Maher Nouiehed; Meisam Razaviyayn (SIAM J. Optim., 2020)

Nonconvex Min-Max Optimization: Applications, Challenges, and Recent Theoretical Advances. - Meisam Razaviyayn; Tianjian Huang; Songtao Lu; Maher Nouiehed; Maziar Sanjabi; Mingyi Hong 001 (IEEE Signal Process. Mag., 2020)

The Internet of Federated Things (IoFT). - Raed Kontar; Naichen Shi; Xubo Yue; Seokhyun Chung; Eunshin Byon; Mosharaf Chowdhury; Jionghua Jin 001; Wissam Kontar; Neda Masoud; Maher Nouiehed; Chinedum Emmanuel Okwudire; Garvesh Raskutti; et al. (IEEE Access, 2021)

GIFAIR-FL: An Approach for Group and Individual Fairness in Federated Learning. - Xubo Yue; Maher Nouiehed; Raed Al Kontar (CoRR, 2021)

The Internet of Federated Things (IoFT): A Vision for the Future and In-depth Survey of Data-driven Approaches for Federated Learning. - Raed Kontar; Naichen Shi; Xubo Yue; Seokhyun Chung; Eunshin Byon; Mosharaf Chowdhury; Judy Jin; Wissam Kontar; Neda Masoud; Maher Nouiehed; Chinedum Emmanuel Okwudire; Garvesh Raskutti; et al. (CoRR, 2021)

Rethinking Cost-sensitive Classification in Deep Learning via Adversarial Data Augmentation. - Qiyuan Chen; Raed Al Kontar; Maher Nouiehed; Xi Jessie Yang; Corey A. Lester (CoRR, 2022)

Learning Deep Models: Critical Points and Local Openness. - Maher Nouiehed; Meisam Razaviyayn (INFORMS J. Optim., 2022)

SEE-OoD: Supervised Exploration For Enhanced Out-of-Distribution Detection. - Xiaoyang Song; Wenbo Sun; Maher Nouiehed; Raed Al Kontar; Judy Jin (CoRR, 2023)

SALR: Sharpness-Aware Learning Rate Scheduler for Improved Generalization. - Xubo Yue; Maher Nouiehed; Raed Al Kontar (IEEE Trans. Neural Networks Learn. Syst., 2024)