Harsha Nori
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
11
Venues
7
Active years
2018–2024
Best venue rank
A*
Where they publish
Papers
11 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2024 | ICLR | Differentially Private Synthetic Data via Foundation Model APIs 1: Images. | Zinan Lin, Sivakanth Gopi, Janardhan Kulkarni, Harsha Nori, Sergey Yekhanin |
| 2024 | ICML | Differentially Private Synthetic Data via Foundation Model APIs 2: Text. | Chulin Xie, Zinan Lin, Arturs Backurs, Sivakanth Gopi, Da Yu, Huseyin A. Inan, Harsha Nori, Haotian Jiang, Huishuai Zhang, Yin Tat Lee, Bo Li, Sergey Yekhanin |
| 2023 | AIES | Supporting Human-AI Collaboration in Auditing LLMs with LLMs. | Charvi Rastogi, Marco Tlio Ribeiro, Nicholas King, Harsha Nori, Saleema Amershi |
| 2022 | KDD | Why Data Scientists Prefer Glassbox Machine Learning: Algorithms, Differential Privacy, Editing and Bias Mitigation. | Rich Caruana, Harsha Nori |
| 2022 | KDD | Interpretability, Then What? Editing Machine Learning Models to Reflect Human Knowledge and Values. | Zijie J. Wang, Alex Kale, Harsha Nori, Peter Stella, Mark E. Nunnally, Duen Horng Chau, Mihaela Vorvoreanu, Jennifer Wortman Vaughan, Rich Caruana |
| 2022 | USENIX | Primo: Practical Learning-Augmented Systems with Interpretable Models. | Qinghao Hu, Harsha Nori, Peng Sun, Yonggang Wen, Tianwei Zhang |
| 2021 | ICML | Accuracy, Interpretability, and Differential Privacy via Explainable Boosting. | Harsha Nori, Rich Caruana, Zhiqi Bu, Judy Hanwen Shen, Janardhan Kulkarni |
| 2021 | KDD | Interpreting Interpretability: Understanding Data Scientists' Use of Interpretability Tools for Machine Learning. | Harmanpreet Kaur, Harsha Nori, Samuel Jenkins, Rich Caruana, Hanna M. Wallach, Jennifer Wortman Vaughan |
| 2020 | CHI | Interpreting Interpretability: Understanding Data Scientists' Use of Interpretability Tools for Machine Learning. | Harmanpreet Kaur, Harsha Nori, Samuel Jenkins, Rich Caruana, Hanna M. Wallach, Jennifer Wortman Vaughan |
| 2020 | KDD | Intelligible and Explainable Machine Learning: Best Practices and Practical Challenges. | Rich Caruana, Scott M. Lundberg, Marco Tlio Ribeiro, Harsha Nori, Samuel Jenkins |
| 2018 | AAAI | Comparing Population Means Under Local Differential Privacy: With Significance and Power. | Bolin Ding, Harsha Nori, Paul Li, Joshua Allen |