| Tangent space estimation for smooth embeddings of Riemannian manifolds ® H Tyagi, E Vural, P Frossard Information and Inference: A Journal of the IMA 2 (1), 69-114, 2013 | 72 | 2013 |
| SPONGE: A generalized eigenproblem for clustering signed networks M Cucuringu, P Davies, A Glielmo, H Tyagi The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 67 | 2019 |
| Automatic identification of bird calls using spectral ensemble average voice prints H Tyagi, RM Hegde, HA Murthy, A Prabhakar 2006 14th European Signal Processing Conference, 1-5, 2006 | 62 | 2006 |
| Learning non-parametric basis independent models from point queries via low-rank methods H Tyagi, V Cevher Applied and Computational Harmonic Analysis 37 (3), 389-412, 2014 | 49 | 2014 |
| Sparse non-negative super-resolution—simplified and stabilised A Eftekhari, J Tanner, A Thompson, B Toader, H Tyagi Applied and Computational Harmonic Analysis 50, 216-280, 2021 | 34 | 2021 |
| Active learning of multi-index function models T Hemant, V Cevher Advances in Neural Information Processing Systems 25, 1475-1483, 2012 | 27 | 2012 |
| On denoising modulo 1 samples of a function M Cucuringu, H Tyagi International Conference on Artificial Intelligence and Statistics, 1868-1876, 2018 | 24 | 2018 |
| Ranking and synchronization from pairwise measurements via SVD A d'Aspremont, M Cucuringu, H Tyagi Journal of Machine Learning Research 22 (19), 1-63, 2021 | 21 | 2021 |
| Regularized spectral methods for clustering signed networks M Cucuringu, AV Singh, D Sulem, H Tyagi Journal of Machine Learning Research 22 (264), 1-79, 2021 | 18 | 2021 |
| Continuum armed bandit problem of few variables in high dimensions H Tyagi, B Gärtner 11th Workshop on Approximation and Online Algorithms 8447, 108-119, 2013 | 17 | 2013 |
| Provably robust estimation of modulo 1 samples of a smooth function with applications to phase unwrapping M Cucuringu, H Tyagi Journal of Machine Learning Research 21 (32), 1-77, 2020 | 14 | 2020 |
| An iterative clustering algorithm for the contextual stochastic block model with optimality guarantees G Braun, H Tyagi, C Biernacki International Conference on Machine Learning, 2257-2291, 2022 | 12 | 2022 |
| Learning sparse additive models with interactions in high dimensions H Tyagi, A Kyrillidis, B Gärtner, A Krause Artificial intelligence and statistics, 111-120, 2016 | 12 | 2016 |
| Efficient sampling for learning sparse additive models in high dimensions H Tyagi, B Gärtner, A Krause Advances in neural information processing systems 27, 2014 | 12 | 2014 |
| Learning ridge functions with randomized sampling in high dimensions H Tyagi, V Cevher 2012 IEEE International Conference on Acoustics, Speech and Signal …, 2012 | 12 | 2012 |
| Denoising modulo samples: k-NN regression and tightness of SDP relaxation M Fanuel, H Tyagi Information and Inference: A Journal of the IMA 11 (2), 637-677, 2022 | 10 | 2022 |
| Clustering multilayer graphs with missing nodes G Braun, H Tyagi, C Biernacki International Conference on Artificial Intelligence and Statistics, 2260-2268, 2021 | 8 | 2021 |
| An extension of the angular synchronization problem to the heterogeneous setting M Cucuringu, H Tyagi arXiv preprint arXiv:2012.14932, 2020 | 8 | 2020 |
| Algorithms for learning sparse additive models with interactions in high dimensions* H Tyagi, A Kyrillidis, B Gärtner, A Krause Information and Inference: A Journal of the IMA 7 (2), 183-249, 2018 | 7 | 2018 |
| Minimax optimal clustering of bipartite graphs with a generalized power method G Braun, H Tyagi Information and Inference: A Journal of the IMA 12 (3), 1830-1866, 2023 | 6 | 2023 |
Mihai CucuringuDepartment of Statistics and Mathematical Institute, University of Oxford; The Alan Turing Institute在 stats.ox.ac.uk 的电子邮件经过验证
