Grants per year
Personal profile
Research Interests
His research interests are broadly in the field of Theoretical Computer Science, particularly, in designing efficient algorithms for problems in Combinatorial Optimization and Machine Learning. He is also interested in using paradigms that go Beyond Worst-Case Analysis to obtain good algorithmic guarantees.
Education/Academic qualification
Computer Science, PhD, Princeton University
… → 2012
Computer Science, MA, Princeton University
… → 2009
Computer Science and Engineering, BTech, Indian Institute of Technology, Madras
… → 2007
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Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Small: New Directions in Community Detection
Gaudio, J. & Vijayaraghavan, A.
10/1/22 → 9/30/25
Project: Research project
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Institute for Data, Econometrics, Algorithms and Learning (IDEAL)
Vijayaraghavan, A., Berry, R. A., Hartline, J. D., Khuller, S., Nocedal, J., Auerbach, E. J., Auffinger, A., Bugni, F. A., Canay, I. A., Gaudio, J., Golub, B., Guo, D., Horowitz, J. L., Hullman, J. R., Liang, A., Linna Jr., D. W., Makarychev, K., Wang, Z. & Wei, E.
9/1/22 → 8/31/27
Project: Research project
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Subproject: Participant Support Costs for Institute for Data, Econometrics, Algorithms and Learning (IDEAL)
9/1/22 → 8/31/27
Project: Research project
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PSC for CAREER: Beyond Worst-Case Analysis: New Approaches in Approximation Algorithms and Machine Learning
3/15/17 → 2/28/23
Project: Research project
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CAREER: Beyond Worst-Case Analysis: New Approaches in Approximation Algorithms and Machine Learning
3/15/17 → 2/28/23
Project: Research project
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EFFECTIVE AND INCONSPICUOUS OVER-THE-AIR ADVERSARIAL EXAMPLES WITH ADAPTIVE FILTERING
O'Reilly, P., Awasthi, P., Vijayaraghavan, A. & Pardo, B., 2022, 2022 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Proceedings. Institute of Electrical and Electronics Engineers Inc., p. 6607-6611 5 p. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; vol. 2022-May).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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Smoothed analysis for tensor methods in unsupervised learning
Bhaskara, A., Chen, A., Perreault, A. & Vijayaraghavan, A., Jun 2022, In: Mathematical Programming. 193, 2, p. 549-599 51 p.Research output: Contribution to journal › Article › peer-review
1 Scopus citations -
Efficient Algorithms for Learning Depth-2 Neural Networks with General ReLU Activations
Awasthi, P., Tang, A. & Vijayaraghavan, A., 2021, Advances in Neural Information Processing Systems 34 - 35th Conference on Neural Information Processing Systems, NeurIPS 2021. Ranzato, MA., Beygelzimer, A., Dauphin, Y., Liang, P. S. & Wortman Vaughan, J. (eds.). Neural information processing systems foundation, p. 13485-13496 12 p. (Advances in Neural Information Processing Systems; vol. 16).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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Adversarial robustness via robust low rank representations
Awasthi, P., Jain, H., Rawat, A. S. & Vijayaraghavan, A., 2020, In: Advances in Neural Information Processing Systems. 2020-DecemberResearch output: Contribution to journal › Conference article › peer-review
2 Scopus citations -
Block stability for map inference
Lang, H., Sontag, D. & Vijayaraghavan, A., 2020.Research output: Contribution to conference › Paper › peer-review
1 Scopus citations