| The more, the merrier: the blessing of dimensionality for learning large Gaussian mixtures J Anderson, M Belkin, N Goyal, L Rademacher, J Voss Conference on Learning Theory, 1135-1164, 2014 | 104 | 2014 |
| Efficient learning of simplices J Anderson, N Goyal, L Rademacher Conference on Learning Theory, 1020-1045, 2013 | 24 | 2013 |
| Introducing... the ambisonic toolkit J Anderson Ambiosnics Symposium 2009, 2009 | 13 | 2009 |
| Heavy-tailed analogues of the covariance matrix for ICA J Anderson, N Goyal, A Nandi, L Rademacher Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 5 | 2017 |
| Heavy-tailed independent component analysis J Anderson, N Goyal, A Nandi, L Rademacher 2015 IEEE 56th Annual Symposium on Foundations of Computer Science, 290-309, 2015 | 5 | 2015 |
| Efficiency of the floating body as a robust measure of dispersion J Anderson, L Rademacher Proceedings of the Fourteenth Annual ACM-SIAM Symposium on Discrete …, 2020 | 3 | 2020 |
| FPGA implementation of graph cut based image thresholding J Anderson, M Gundam, A Joginipelly, D Charalampidis Proceedings of the 2012 44th Southeastern Symposium on System Theory (SSST …, 2012 | 2 | 2012 |
| Geometric Methods for Robust Data Analysis in High Dimension J Anderson arXiv preprint arXiv:1705.09269, 2017 | | 2017 |
Luis RademacherDepartment of Mathematics, UC DavisVerified email at math.ucdavis.edu
