Detecting high log-densities: an O(n¼) approximation for densest k-subgraph A Bhaskara, M Charikar, E Chlamtac, U Feige, A Vijayaraghavan Proceedings of the forty-second ACM symposium on Theory of computing, 201-210, 2010 | 405 | 2010 |
Smoothed analysis of tensor decompositions A Bhaskara, M Charikar, A Moitra, A Vijayaraghavan Proceedings of the forty-sixth annual ACM symposium on Theory of computing …, 2014 | 173 | 2014 |
Polynomial integrality gaps for strong SDP relaxations of Densest k-subgraph A Bhaskara, M Charikar, V Guruswami, A Vijayaraghavan, Y Zhou Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete …, 2012 | 138 | 2012 |
On learning mixtures of well-separated gaussians O Regev, A Vijayaraghavan 2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS), 85-96, 2017 | 101 | 2017 |
Beating the random assignment on constraint satisfaction problems of bounded degree B Barak, A Moitra, R O'Donnell, P Raghavendra, O Regev, D Steurer, ... arXiv preprint arXiv:1505.03424, 2015 | 90 | 2015 |
Learning mixtures of ranking models P Awasthi, A Blum, O Sheffet, A Vijayaraghavan Advances in Neural Information Processing Systems 27, 2014 | 90 | 2014 |
Approximation algorithms for semi-random partitioning problems K Makarychev, Y Makarychev, A Vijayaraghavan Proceedings of the forty-fourth annual ACM symposium on Theory of computing …, 2012 | 77 | 2012 |
Uniqueness of tensor decompositions with applications to polynomial identifiability A Bhaskara, M Charikar, A Vijayaraghavan Conference on Learning Theory (COLT) 2014 35, 742–778, 2014 | 75 | 2014 |
Bilu–Linial stable instances of max cut and minimum multiway cut K Makarychev, Y Makarychev, A Vijayaraghavan Proceedings of the twenty-fifth annual ACM-SIAM symposium on Discrete …, 2014 | 71 | 2014 |
Approximating Matrix p-norms A Bhaskara, A Vijayaraghavan Proceedings of the twenty-second annual ACM-SIAM symposium on Discrete …, 2011 | 61 | 2011 |
Correlation clustering with noisy partial information K Makarychev, Y Makarychev, A Vijayaraghavan Conference on Learning Theory, 1321-1342, 2015 | 51 | 2015 |
On robustness to adversarial examples and polynomial optimization P Awasthi, A Dutta, A Vijayaraghavan Advances in Neural Information Processing Systems 32, 2019 | 41 | 2019 |
Approximation Algorithms and Hardness of the k-Route Cut Problem J Chuzhoy, Y Makarychev, A Vijayaraghavan, Y Zhou ACM Transactions on Algorithms (TALG) 12 (1), 1-40, 2015 | 41 | 2015 |
Learning communities in the presence of errors K Makarychev, Y Makarychev, A Vijayaraghavan Conference on learning theory, 1258-1291, 2016 | 40 | 2016 |
Constant factor approximation for balanced cut in the PIE model K Makarychev, Y Makarychev, A Vijayaraghavan Proceedings of the forty-sixth annual ACM symposium on Theory of computing …, 2014 | 34 | 2014 |
Clustering Stable Instances of Euclidean k-means. A Vijayaraghavan, A Dutta, A Wang Advances in Neural Information Processing Systems 30, 2017 | 32 | 2017 |
Adversarial robustness via robust low rank representations P Awasthi, H Jain, AS Rawat, A Vijayaraghavan Advances in Neural Information Processing Systems 33, 11391-11403, 2020 | 26 | 2020 |
Smoothed analysis for tensor methods in unsupervised learning A Bhaskara, A Chen, A Perreault, A Vijayaraghavan Mathematical Programming, 1-51, 2022 | 24* | 2022 |
Sorting noisy data with partial information K Makarychev, Y Makarychev, A Vijayaraghavan Proceedings of the 4th conference on Innovations in Theoretical Computer …, 2013 | 24 | 2013 |
Efficient algorithms for learning depth-2 neural networks with general relu activations P Awasthi, A Tang, A Vijayaraghavan Advances in Neural Information Processing Systems 34, 13485-13496, 2021 | 23 | 2021 |