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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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AF: Small: Linear Algebra++ and Applications to Machine Learning
NSF - National Science Foundation
6/15/15 → 5/31/19
Project: Research project
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AF: Medium: Towards Provable Bounds for Machine Learning
NSF - National Science Foundation
9/1/13 → 8/31/17
Project: Research project
Research output
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Why don't today's deep nets overfit to their training data?
Arora, S., Mar 2021, In: Communications of the ACM. 64, 3, p. 106 1 p.Research output: Contribution to journal › Comment/debate › peer-review
Open Access -
A sample complexity separation between non-convex and convex meta-learning
Saunshi, N., Zhang, Y., Khodak, M. & Arora, S., 2020, 37th International Conference on Machine Learning, ICML 2020. Daume, H. & Singh, A. (eds.). International Machine Learning Society (IMLS), p. 8470-8479 10 p. (37th International Conference on Machine Learning, ICML 2020; vol. PartF168147-11).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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InstaHide: Instance-hiding schemes for private distributed learning
Huang, Y., Song, Z., Li, K. & Arora, S., 2020, 37th International Conference on Machine Learning, ICML 2020. Daume, H. & Singh, A. (eds.). International Machine Learning Society (IMLS), p. 4457-4468 12 p. (37th International Conference on Machine Learning, ICML 2020; vol. PartF168147-6).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
3 Scopus citations -
Over-parameterized adversarial training: An analysis overcoming the curse of dimensionality
Zhang, Y., Plevrakis, O., Du, S. S., Li, X., Song, Z. & Arora, S., 2020, In: Advances in Neural Information Processing Systems. 2020-DecemberResearch output: Contribution to journal › Conference article › peer-review
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Provable representation learning for imitation learning via bi-level optimization
Arora, S., Du, S. S., Kakade, S., Luo, Y. & Saunshi, N., 2020, 37th International Conference on Machine Learning, ICML 2020. Daume, H. & Singh, A. (eds.). International Machine Learning Society (IMLS), p. 344-353 10 p. (37th International Conference on Machine Learning, ICML 2020; vol. PartF168147-1).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
1 Scopus citations