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
2009 → 2012
Computer Science, MA, Princeton University
2007 → 2009
Computer Science and Engineering, BTech, Indian Institute of Technology, Madras
2003 → 2007
Fingerprint Dive into the research topics where Aravindan Vijayaraghavan is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
- 1 Similar Profiles
Approximation algorithms
Engineering & Materials Science
Approximation Algorithms
Mathematics
Polynomials
Engineering & Materials Science
Tensors
Engineering & Materials Science
Tensor Decomposition
Mathematics
Hardness
Mathematics
Decomposition
Engineering & Materials Science
Max-cut
Mathematics
Network
Recent external collaboration on country level. Dive into details by clicking on the dots.
Grants 2016 2022
- 4 Active
HDR TRIPODS: Collaborative Research: Institute for Data, Econometrics, Algorithms and Learning .
Hartline, J. D., Auerbach, E. J., Berry, R. A., Canay, I. A., Guo, D., Horowitz, J. L., Makarychev, K., Vijayaraghavan, A. & Wang, Z.
9/15/19 → 8/31/22
Project: Research project
Learning systems
Operations research
Unsupervised learning
Engineering research
Electrical engineering
CAREER: Beyond Worst-Case Analysis: New Approaches in Approximation Algorithms and Machine Learning
3/15/17 → 2/28/22
Project: Research project
Approximation algorithms
Learning systems
Combinatorial optimization
Computer science
Students
PSC for CAREER: Beyond Worst-Case Analysis: New Approaches in Approximation Algorithms and Machine Learning
3/15/17 → 2/28/22
Project: Research project
Learning systems
Combinatorial optimization
Computer science
Students
Unsupervised learning
AitF: Collaborative Research: Algorithms for Probabilistic Inference in the Real World
9/1/16 → 8/31/20
Project: Research project
Learning systems
Combinatorial optimization
Computer vision
Structural properties
Approximation algorithms
Research Output 2010 2018
Clustering semi-random mixtures of Gaussians
Awasthi, P. & Vijayaraghavan, A., Jan 1 2018, 35th International Conference on Machine Learning, ICML 2018. Krause, A. & Dy, J. (eds.). International Machine Learning Society (IMLS), p. 469-494 26 p. (35th International Conference on Machine Learning, ICML 2018; vol. 1).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Clustering algorithms
Polynomials
Statistical Models
Editorial: ACM-SIAM symposium on discrete algorithms (SODA) 2016 special issue
Bhattacharyya, A., Grandoni, F., Nikolov, A., Saha, B., Saurabh, S., Vijayaraghavan, A. & Zhang, Q., Jul 1 2018, In : ACM Transactions on Algorithms. 14, 3, 26.Research output: Contribution to journal › Editorial
Optimality of approximate inference algorithms on stable instances
Lang, H., Sontag, D. & Vijayaraghavan, A., Jan 1 2018, p. 1157-1166. 10 p.Research output: Contribution to conference › Paper
Optimality
LP Relaxation
Performance Guarantee
Approximate Algorithm
Potts model
Towards learning sparsely used dictionaries with arbitrary supports
Awasthi, P. & Vijayaraghavan, A., Nov 30 2018, Proceedings - 59th Annual IEEE Symposium on Foundations of Computer Science, FOCS 2018. Thorup, M. (ed.). IEEE Computer Society, p. 283-296 14 p. 8555113. (Proceedings - Annual IEEE Symposium on Foundations of Computer Science, FOCS; vol. 2018-October).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Glossaries
Polynomials
Byproducts
Approximation algorithms for label cover and the log-density threshold
Chlamtáč, E., Manurangsi, P., Moshkovitz, D. & Vijayaraghavan, A., Jan 1 2017, 28th Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2017. Klein, P. N. (ed.). Association for Computing Machinery, p. 900-919 20 p. (Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Approximation algorithms
Labels
Approximation Algorithms
Projection
Cover