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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Collaborations and top research areas from the last five years
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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., Vijayaraghavan, A., Berry, R. A., Berry, R. A., Hartline, J. D., Hartline, J. D., Khuller, S., Khuller, S., Nocedal, J., Nocedal, J., Auerbach, E. J., Auerbach, E. J., Auffinger, A., Auffinger, A., Bugni, F. A., Bugni, F. A., Canay, I. A., Canay, I. A., Gaudio, J., Gaudio, J., Golub, B., Golub, B., Guo, D., Guo, D., Horowitz, J. L., Horowitz, J. L., Hullman, J. R., Hullman, J. R., Liang, A., Liang, A., Linna Jr., D. W., Linna Jr., D. W., Makarychev, K., Makarychev, K., Wang, Z., Wang, Z., Wei, E. & Wei, E.
9/1/22 → 8/31/27
Project: Research project
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CAREER: Beyond Worst-Case Analysis: New Approaches in Approximation Algorithms and Machine Learning
3/15/17 → 2/29/24
Project: Research project
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HDR TRIPODS: Collaborative Research: Institute for Data, Econometrics, Algorithms and Learning
Hartline, J. D., Berry, R. A., Canay, I. A., Vijayaraghavan, A., Wang, Z., Auerbach, E. J., Guo, D., Horowitz, J. L., Khuller, S. & Makarychev, K.
9/15/19 → 8/31/23
Project: Research project
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AitF: Collaborative Research: Algorithms for Probabilistic Inference in the Real World
9/1/16 → 8/31/22
Project: Research project
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Algorithms for learning a mixture of linear classifiers
Chen, A., De, A. & Vijayaraghavan, A., 2022, In: Proceedings of Machine Learning Research. 167, p. 205-226 22 p.Research output: Contribution to journal › Conference article › peer-review
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Classification Protocols with Minimal Disclosure
Dong, J., Hartline, J. & Vijayaraghavan, A., Nov 1 2022, CSLAW 2022 - Proceedings of the 2022 Symposium on Computer Science and Law. Association for Computing Machinery, Inc, p. 67-76 10 p. (CSLAW 2022 - Proceedings of the 2022 Symposium on Computer Science and Law).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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Complete hierarchy of linear systems for certifying quantum entanglement of subspaces
Johnston, N., Lovitz, B. & Vijayaraghavan, A., Dec 2022, In: Physical Review A. 106, 6, 062443.Research output: Contribution to journal › Article › peer-review
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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
1 Scopus citations -
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