| Consistency of spectral hypergraph partitioning under planted partition model D Ghoshdastidar, A Dukkipati The Annals of Statistics 45 (1), 289-315, 2017 | 99 | 2017 |
| Consistency of spectral partitioning of uniform hypergraphs under planted partition model D Ghoshdastidar, A Dukkipati Advances in Neural Information Processing Systems 27, 2014 | 96 | 2014 |
| A provable generalized tensor spectral method for uniform hypergraph partitioning D Ghoshdastidar, A Dukkipati International Conference on Machine Learning, 400-409, 2015 | 53 | 2015 |
| Two-sample Hypothesis Testing for Inhomogeneous Random Graphs D Ghoshdastidar, M Gutzeit, A Carpentier, U von Luxburg Annals of Statistics 48 (4), 2208-2229, 2020 | 50 | 2020 |
| Uniform hypergraph partitioning: Provable tensor methods and sampling techniques D Ghoshdastidar, A Dukkipati The Journal of Machine Learning Research 18 (1), 1638-1678, 2017 | 50 | 2017 |
| Two-sample tests for large random graphs using network statistics D Ghoshdastidar, M Gutzeit, A Carpentier, U von Luxburg Conference on Learning Theory (COLT) 65, 954-977, 2017 | 47 | 2017 |
| Comparison based nearest neighbor search S Haghiri, D Ghoshdastidar, U von Luxburg International Conference on Artificial Intelligence and Statistics (AISTATS …, 2017 | 40 | 2017 |
| Practical methods for graph two-sample testing D Ghoshdastidar, U Von Luxburg Advances in Neural Information Processing Systems 31, 2018 | 37 | 2018 |
| Spectral clustering using multilinear SVD: Analysis, approximations and applications D Ghoshdastidar, A Dukkipati Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015 | 31 | 2015 |
| Foundations of comparison-based hierarchical clustering D Ghoshdastidar, M Perrot, U von Luxburg Advances in neural information processing systems 32, 2019 | 28 | 2019 |
| HOLISMOKES-VII. Time-delay measurement of strongly lensed Type Ia supernovae using machine learning S Huber, SH Suyu, D Ghoshdastidar, S Taubenberger, V Bonvin, ... Astronomy & Astrophysics 658, A157, 2022 | 17 | 2022 |
| Learning theory can (sometimes) explain generalisation in graph neural networks P Esser, L Chennuru Vankadara, D Ghoshdastidar Advances in Neural Information Processing Systems 34, 27043-27056, 2021 | 16 | 2021 |
| On the optimality of kernels for high-dimensional clustering LC Vankadara, D Ghoshdastidar International Conference on Artificial Intelligence and Statistics, 2185-2195, 2020 | 11 | 2020 |
| Smoothed Functional Algorithms for Stochastic Optimization Using q-Gaussian Distributions D Ghoshdastidar, A Dukkipati, S Bhatnagar ACM Transactions on Modeling and Computer Simulation (TOMACS) 24 (3), 1-26, 2014 | 9 | 2014 |
| q-Gaussian based smoothed functional algorithms for stochastic optimization D Ghoshdastidar, A Dukkipati, S Bhatnagar 2012 IEEE International Symposium on Information Theory Proceedings, 1059-1063, 2012 | 9 | 2012 |
| Mixture modeling with compact support distributions for unsupervised learning A Dukkipati, D Ghoshdastidar, J Krishnan 2016 International Joint Conference on Neural Networks (IJCNN), 2706-2713, 2016 | 7 | 2016 |
| Graphon based clustering and testing of networks: Algorithms and theory M Sabanayagam, LC Vankadara, D Ghoshdastidar arXiv preprint arXiv:2110.02722, 2021 | 6 | 2021 |
| Near-optimal comparison based clustering M Perrot, P Esser, D Ghoshdastidar Advances in Neural Information Processing Systems 33, 19388-19399, 2020 | 6 | 2020 |
| Representation Power of Graph Convolutions: Neural Tangent Kernel Analysis M Sabanayagam, P Esser, D Ghoshdastidar arXiv preprint arXiv:2210.09809, 2022 | 5 | 2022 |
| Learning With Jensen-Tsallis Kernels D Ghoshdastidar, AP Adsul, A Dukkipati IEEE Transactions on Neural Networks and Learning Systems 27 (10), 2108-2119, 2016 | 5 | 2016 |
Ambedkar DukkipatiProfessor, Department of Computer Science and Automation, Indian Institute of ScienceVerified email at iisc.ac.in
