| When do random forests fail? C Tang, D Garreau, U von Luxburg Advances in neural information processing systems 31, 2018 | 103 | 2018 |
| Exponentially convergent stochastic k-PCA without variance reduction C Tang Advances in Neural Information Processing Systems 32, 2019 | 33 | 2019 |
| On Lloyd’s algorithm: new theoretical insights for clustering in practice C Tang, C Monteleoni Artificial Intelligence and Statistics, 1280-1289, 2016 | 29 | 2016 |
| Convergence rate of stochastic k-means C Tang, C Monteleoni Artificial Intelligence and Statistics, 1495-1503, 2017 | 23 | 2017 |
| Can topic modeling shed light on climate extremes? C Tang, C Monteleoni Computing in Science & Engineering 17 (6), 43-52, 2015 | 6 | 2015 |
| On the convergence rate of stochastic gradient descent for strongly convex functions C Tang, C Monteleoni Regularization, optimization, kernels, and support vector machines, 159-175, 2015 | 4 | 2015 |
| Detecting extreme events from climate time series via topic modeling C Tang, C Monteleoni Machine Learning and Data Mining Approaches to Climate Science: Proceedings …, 2015 | 4 | 2015 |
| Neural document expansion for ad-hoc information retrieval C Tang, A Arnold arXiv preprint arXiv:2012.14005, 2020 | 2 | 2020 |
| Demystifying overcomplete nonlinear auto-encoders: fast SGD convergence towards sparse representation from random initialization C Tang, C Monteleoni | 2 | 2018 |
| Convergence analysis of stochastic gradient descent on strongly convex objective functions C Tang, C Monteleoni Proceedings of ROKS, 111-112, 2013 | 1 | 2013 |
| Scalable constant k-means approximation via heuristics on well-clusterable data C Tang, C Monteleoni Poster Session of Learning faster from easy data II conference, Montreal, Canada, 0 | 1 | |
| On the tightness of linear relaxation based robustness certification methods C Tang arXiv preprint arXiv:2210.00178, 2022 | | 2022 |
| Transforming Machine Learning Heuristics into Provable Algorithms: Classical, Stochastic, and Neural C Tang The George Washington University, 2018 | | 2018 |
| HOW FAR CAN WE EXPLOIT THE STRUCTURAL RICHNESS OF CLIMATE DATA?—A CASE STUDY M Mohan, C Tang, C Monteleoni, T DelSole, B Cash | | |
| Scaling up Lloyd’s algorithm: stochastic and parallel block-wise optimization perspectives C Tang, C Monteleoni | | |
| Seasonal prediction using unsupervised feature learning and regression M Mohan, C Tang, C Monteleoni, T DelSole, B Cash | | |
Damien GarreauAssociate Professor, Université Côte d'Azur (France)Verified email at unice.fr
