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Hussein Mozannar
Hussein Mozannar
Microsoft Research
Verified email at microsoft.com - Homepage
Title
Cited by
Cited by
Year
Consistent estimators for learning to defer to an expert
H Mozannar, D Sontag
International conference on machine learning, 7076-7087, 2020
2292020
Neural Arabic Question Answering
H Mozannar, KE Hajal, E Maamary, H Hajj
Proceedings of the Fourth Arabic Natural Language Processing Workshop, 108–118, 2019
1612019
Damage Identification in Social Media Posts using Multimodal Deep Learning
H Mouzannar, Y Rizk, M Awad
ISCRAM 2018 – 15th International Conference on Information Systems for …, 2018
1512018
From fair decision making to social equality
H Mouzannar, MI Ohannessian, N Srebro
Proceedings of the Conference on Fairness, Accountability, and Transparency …, 2019
1172019
Reading between the lines: Modeling user behavior and costs in AI-assisted programming
H Mozannar, G Bansal, A Fourney, E Horvitz
CHI 2024, 2022
105*2022
Fair learning with private demographic data
H Mozannar, M Ohannessian, N Srebro
International Conference on Machine Learning, 7066-7075, 2020
882020
Teaching humans when to defer to a classifier via exemplars
H Mozannar, A Satyanarayan, D Sontag
Proceedings of the AAAI Conference on Artificial Intelligence 36 (5), 5323-5331, 2022
552022
Who Should Predict? Exact Algorithms For Learning to Defer to Humans
H Mozannar, H Lang, D Wei, P Sattigeri, S Das, D Sontag
International Conference on Artificial Intelligence and Statistics, 10520-10545, 2023
392023
Sample efficient learning of predictors that complement humans
MA Charusaie, H Mozannar, D Sontag, S Samadi
International Conference on Machine Learning, 2972-3005, 2022
372022
When to show a suggestion? Integrating human feedback in AI-assisted programming
H Mozannar, G Bansal, A Fourney, E Horvitz
Proceedings of the AAAI Conference on Artificial Intelligence 38 (9), 10137 …, 2024
27*2024
In defense of softmax parametrization for calibrated and consistent learning to defer
Y Cao, H Mozannar, L Feng, H Wei, B An
Advances in Neural Information Processing Systems 36, 2024
132024
Effective human-AI teams via learned natural language rules and onboarding
H Mozannar, J Lee, D Wei, P Sattigeri, S Das, D Sontag
Advances in Neural Information Processing Systems 36, 2024
132024
The RealHumanEval: Evaluating Large Language Models' Abilities to Support Programmers
H Mozannar, V Chen, M Alsobay, S Das, S Zhao, D Wei, M Nagireddy, ...
arXiv preprint arXiv:2404.02806, 2024
7*2024
Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium
H Jeong, S Jabbour, Y Yang, R Thapta, H Mozannar, WJ Han, ...
arXiv preprint arXiv:2403.01628, 2024
22024
Impact of Large Language Model Assistance on Patients Reading Clinical Notes: A Mixed-Methods Study
N Mannhardt, E Bondi-Kelly, B Lam, H Mozannar, C O'Connell, M Asiedu, ...
arXiv preprint arXiv:2401.09637, 2024
22024
Magentic-One: A Generalist Multi-Agent System for Solving Complex Tasks
A Fourney, G Bansal, H Mozannar, C Tan, E Salinas, F Niedtner, ...
arXiv preprint arXiv:2411.04468, 2024
2024
Need Help? Designing Proactive AI Assistants for Programming
V Chen, A Zhu, S Zhao, H Mozannar, D Sontag, A Talwalkar
arXiv preprint arXiv:2410.04596, 2024
2024
Training Human-AI Teams
H Mozannar
Massachusetts Institute of Technology, 2024
2024
Simulating Iterative Human-AI Interaction in Programming with LLMs
H Mozannar, V Chen, D Wei, P Sattigeri, M Nagireddy, S Das, A Talwalkar, ...
NeurIPS 2023 Workshop on Instruction Tuning and Instruction Following, 2023
2023
Closing the Gap in High-Risk Pregnancy Care Using Machine Learning and Human-AI Collaboration
H Mozannar, Y Utsumi, IY Chen, SS Gervasi, M Ewing, A Smith-McLallen, ...
arXiv preprint arXiv:2305.17261, 2023
2023
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