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Harsha Nori
Harsha Nori
Microsoft Research
Verified email at microsoft.com - Homepage
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Cited by
Cited by
Year
Sparks of artificial general intelligence: Early experiments with gpt-4
S Bubeck, V Chandrasekaran, R Eldan, J Gehrke, E Horvitz, E Kamar, ...
arXiv preprint arXiv:2303.12712, 2023
25762023
Interpretml: A unified framework for machine learning interpretability
H Nori, S Jenkins, P Koch, R Caruana
arXiv preprint arXiv:1909.09223, 2019
5682019
Capabilities of gpt-4 on medical challenge problems
H Nori, N King, SM McKinney, D Carignan, E Horvitz
arXiv preprint arXiv:2303.13375, 2023
5582023
Interpreting interpretability: understanding data scientists' use of interpretability tools for machine learning
H Kaur, H Nori, S Jenkins, R Caruana, H Wallach, J Wortman Vaughan
Proceedings of the 2020 CHI conference on human factors in computing systems …, 2020
5342020
Can generalist foundation models outcompete special-purpose tuning? case study in medicine
H Nori, YT Lee, S Zhang, D Carignan, R Edgar, N Fusi, N King, J Larson, ...
arXiv preprint arXiv:2311.16452, 2023
1212023
Supporting human-ai collaboration in auditing llms with llms
C Rastogi, M Tulio Ribeiro, N King, H Nori, S Amershi
Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 913-926, 2023
492023
Sparks of artificial general intelligence: Early experiments with gpt-4. arXiv 2023
S Bubeck, V Chandrasekaran, R Eldan, J Gehrke, E Horvitz, E Kamar, ...
arXiv preprint arXiv:2303.12712 10, 0
49
An algorithmic framework for differentially private data analysis on trusted processors
J Allen, B Ding, J Kulkarni, H Nori, O Ohrimenko, S Yekhanin
Advances in Neural Information Processing Systems 32, 2019
442019
Accuracy, Interpretability, and Differential Privacy via Explainable Boosting
H Nori, R Caruana, Z Bu, JH Shen, J Kulkarni
Proceedings of the 38th International Conference on Machine Learning 139 …, 2021
432021
Intelligible and explainable machine learning: Best practices and practical challenges
R Caruana, S Lundberg, MT Ribeiro, H Nori, S Jenkins
Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020
412020
Comparing population means under local differential privacy: with significance and power
B Ding, H Nori, P Li, J Allen
Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018
372018
Gam changer: Editing generalized additive models with interactive visualization
ZJ Wang, A Kale, H Nori, P Stella, M Nunnally, DH Chau, M Vorvoreanu, ...
arXiv preprint arXiv:2112.03245, 2021
282021
Interpretability, then what? editing machine learning models to reflect human knowledge and values
ZJ Wang, A Kale, H Nori, P Stella, ME Nunnally, DH Chau, M Vorvoreanu, ...
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022
242022
Proceedings of the 2020 CHI conference on human factors in computing systems
H Kaur, H Nori, S Jenkins, R Caruana, H Wallach, J Wortman Vaughan
192020
Remote validation of machine-learning models for data imbalance
CL Weider, R Kikin-Gil, HP Nori
US Patent 11,537,941, 2022
132022
Differentially private estimation of heterogeneous causal effects
F Niu, H Nori, B Quistorff, R Caruana, D Ngwe, A Kannan
Conference on Causal Learning and Reasoning, 618-633, 2022
122022
Using explainable boosting machines (ebms) to detect common flaws in data
Z Chen, S Tan, H Nori, K Inkpen, Y Lou, R Caruana
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2021
112021
Method and System of Correcting Data Imbalance in a Dataset Used in Machine-Learning
CL Weider, R Kikin-Gil, HP Nori
US Patent App. 16/424,371, 2020
112020
Differentially private synthetic data via foundation model apis 1: Images
Z Lin, S Gopi, J Kulkarni, H Nori, S Yekhanin
arXiv preprint arXiv:2305.15560, 2023
102023
Method and system of detecting data imbalance in a dataset used in machine-learning
CL Weider, R Kikin-Gil, HP Nori
US Patent 11,521,115, 2022
102022
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