| MLPACK: A scalable C++ machine learning library RR Curtin, JR Cline, NP Slagle, WB March, P Ram, NA Mehta, AG Gray The Journal of Machine Learning Research 14 (1), 801-805, 2013 | 216 | 2013 |
| Fast rates in statistical and online learning T Van Erven, PD Grünwald, NA Mehta, MD Reid, RC Williamson The Journal of Machine Learning Research 16 (1), 1793-1861, 2015 | 114 | 2015 |
| Fast rates for general unbounded loss functions: from ERM to generalized Bayes PD Grünwald, NA Mehta Journal of Machine Learning Research 21 (56), 1-80, 2020 | 83 | 2020 |
| Fast rates with high probability in exp-concave statistical learning N Mehta Artificial Intelligence and Statistics, 1085-1093, 2017 | 48 | 2017 |
| Sparsity-based generalization bounds for predictive sparse coding N Mehta, A Gray International Conference on Machine Learning, 36-44, 2013 | 47 | 2013 |
| A tight excess risk bound via a unified PAC-Bayesian–Rademacher–Shtarkov–MDL complexity PD Grünwald, NA Mehta Algorithmic Learning Theory, 433-465, 2019 | 37 | 2019 |
| Safe-Bayesian generalized linear regression R Heide, A Kirichenko, P Grunwald, N Mehta International Conference on Artificial Intelligence and Statistics, 2623-2633, 2020 | 32 | 2020 |
| On the sample complexity of predictive sparse coding NA Mehta, AG Gray arXiv preprint arXiv:1202.4050, 2012 | 22 | 2012 |
| Generalized mixability via entropic duality MD Reid, RM Frongillo, RC Williamson, N Mehta Conference on Learning Theory, 1501-1522, 2015 | 19 | 2015 |
| Computer detection approaches for the identification of phasic electromyographic (EMG) activity during human sleep JA Fairley, G Georgoulas, NA Mehta, AG Gray, DL Bliwise Biomedical Signal Processing and Control 7 (6), 606-615, 2012 | 18 | 2012 |
| Independent component analysis F Westad, M Kermit Elsevier, 2009 | 18 | 2009 |
| Fast rates with unbounded losses PD Grünwald, NA Mehta arXiv preprint arXiv:1605.00252 2, 14, 2016 | 17 | 2016 |
| Modeling software behavior using learned predicates AX Zheng, MS Musuvathi, NA Mehta US Patent 9,098,621, 2015 | 17 | 2015 |
| From stochastic mixability to fast rates NA Mehta, RC Williamson Advances in Neural Information Processing Systems 27, 2014 | 17 | 2014 |
| Intelligent caching algorithms in heterogeneous wireless networks with uncertainty B Hu, Y Chen, Z Huang, NA Mehta, J Pan 2019 IEEE 39th International Conference on Distributed Computing Systems …, 2019 | 12 | 2019 |
| Optimal algorithms for private online learning in a stochastic environment B Hu, Z Huang, NA Mehta arXiv preprint arXiv:2102.07929, 2021 | 11 | 2021 |
| Problem-dependent regret bounds for online learning with feedback graphs B Hu, NA Mehta, J Pan Uncertainty in Artificial Intelligence, 852-861, 2020 | 11 | 2020 |
| Minimax multi-task learning and a generalized loss-compositional paradigm for MTL N Mehta, D Lee, A Gray Advances in Neural Information Processing Systems 25, 2012 | 11 | 2012 |
| Fast rates for general unbounded loss functions: from ERM to generalized Bayes PD Grünwald, NA Mehta arXiv preprint arXiv:1605.00252, 2016 | 8 | 2016 |
| VisIRR: interactive visual information retrieval and recommendation for large-scale document data J Choo, C Lee, E Clarkson, Z Liu, H Lee, DHP Chau, F Li, R Kannan, ... Georgia Institute of Technology, 2013 | 8 | 2013 |
Peter GrünwaldGroup Leader Machine Learning, CWI; Professor of Statistics, Leiden UniversityVerified email at cwi.nl
