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Dive into the research topics where Sanjeev Arora is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Collaborations and top research areas from the last five years
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Collaborative Research:RI:Medium:MoDL:Mathematical and Conceptual Understanding of Large Language Models
Arora, S. (PI)
NSF - National Science Foundation
10/1/22 → 9/30/25
Project: Research project
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Going beyond a black-box optimization view of deep learning
Arora, S. (PI)
4/7/20 → 10/31/23
Project: Research project
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AF: Large: Collaborative Research: Nonconvex methods and models for learning: Toward algorithms with provable and interpretable guarantees
Arora, S. (PI)
NSF - National Science Foundation
6/1/17 → 5/31/23
Project: Research project
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Unsupervised Learning with Provable Guarantees
Arora, S. (PI)
4/1/16 → 3/31/20
Project: Research project
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AF: Small: Linear Algebra++ and Applications to Machine Learning
Arora, S. (PI)
NSF - National Science Foundation
6/15/15 → 5/31/19
Project: Research project
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Evaluating gradient inversion attacks and defenses
Huang, Y., Gupta, S., Song, Z., Arora, S. & Li, K., Jan 1 2024, Federated Learning: Theory and Practice. Elsevier, p. 105-122 18 p.Research output: Chapter in Book/Report/Conference proceeding › Chapter
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A Kernel-Based View of Language Model Fine-Tuning
Malladi, S., Wettig, A., Yu, D., Chen, D. & Arora, S., 2023, In: Proceedings of Machine Learning Research. 202, p. 23610-23641 32 p.Research output: Contribution to journal › Conference article › peer-review
4 Scopus citations -
Do Transformers Parse while Predicting the Masked Word?
Zhao, H., Panigrahi, A., Ge, R. & Arora, S., 2023, EMNLP 2023 - 2023 Conference on Empirical Methods in Natural Language Processing, Proceedings. Bouamor, H., Pino, J. & Bali, K. (eds.). Association for Computational Linguistics (ACL), p. 16513-16542 30 p. (EMNLP 2023 - 2023 Conference on Empirical Methods in Natural Language Processing, Proceedings).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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Task-Specific Skill Localization in Fine-tuned Language Models
Panigrahi, A., Saunshi, N., Zhao, H. & Arora, S., 2023, In: Proceedings of Machine Learning Research. 202, p. 27011-27033 23 p.Research output: Contribution to journal › Conference article › peer-review
1 Scopus citations -
UNDERSTANDING INFLUENCE FUNCTIONS AND DATAMODELS VIA HARMONIC ANALYSIS
Saunshi, N., Gupta, A., Braverman, M. & Arora, S., 2023.Research output: Contribution to conference › Paper › peer-review
2 Scopus citations