| Stochastically transitive models for pairwise comparisons: Statistical and computational issues N Shah, S Balakrishnan, A Guntuboyina, M Wainwright International Conference on Machine Learning, 11-20, 2016 | 182 | 2016 |
| On risk bounds in isotonic and other shape restricted regression problems S Chatterjee, A Guntuboyina, B Sen | 148 | 2015 |
| Global risk bounds and adaptation in univariate convex regression A Guntuboyina, B Sen Probability Theory and Related Fields 163 (1), 379-411, 2015 | 104 | 2015 |
| Nonparametric shape-restricted regression A Guntuboyina, B Sen Statistical Science 33 (4), 568-594, 2018 | 102 | 2018 |
| Covering numbers for convex functions A Guntuboyina, B Sen IEEE Transactions on Information Theory 59 (4), 1957-1965, 2012 | 91* | 2012 |
| Adaptive risk bounds in univariate total variation denoising and trend filtering A Guntuboyina, D Lieu, S Chatterjee, B Sen | 89* | 2020 |
| Lower Bounds for the Minimax Risk Using -Divergences, and Applications A Guntuboyina IEEE Transactions on Information Theory 57 (4), 2386-2399, 2011 | 88 | 2011 |
| On matrix estimation under monotonicity constraints S Chatterjee, A Guntuboyina, B Sen | 75 | 2018 |
| On the nonparametric maximum likelihood estimator for Gaussian location mixture densities with application to Gaussian denoising S Saha, A Guntuboyina The Annals of Statistics 48 (2), 738-762, 2020 | 67 | 2020 |
| On Bayes risk lower bounds X Chen, Y Zhang Journal of Machine Learning Research 17 (218), 1-58, 2016 | 61 | 2016 |
| Adaptation in log-concave density estimation AKH Kim, A Guntuboyina, RJ Samworth The Annals of Statistics 46 (5), 2279-2306, 2018 | 54 | 2018 |
| Sharp Inequalities for -Divergences A Guntuboyina, S Saha, G Schiebinger IEEE transactions on information theory 60 (1), 104-121, 2013 | 51 | 2013 |
| Optimal rates of convergence for convex set estimation from support functions A Guntuboyina Annals of Statistics 40 (1), 385-411, 2012 | 47 | 2012 |
| Multivariate extensions of isotonic regression and total variation denoising via entire monotonicity and Hardy–Krause variation B Fang, A Guntuboyina, B Sen | 37 | 2021 |
| Max-affine regression: Provable, tractable, and near-optimal statistical estimation A Ghosh, A Pananjady, A Guntuboyina, K Ramchandran arXiv preprint arXiv:1906.09255, 2019 | 32 | 2019 |
| Concentration of the spectral measure of large Wishart matrices with dependent entries A Guntuboyina, H Leeb | 32 | 2009 |
| The geometry of hypothesis testing over convex cones: Generalized likelihood ratio tests and minimax radii Y Wei, MJ Wainwright, A Guntuboyina | 29 | 2019 |
| Convex regression in multidimensions: Suboptimality of least squares estimators G Kur, F Gao, A Guntuboyina, B Sen arXiv preprint arXiv:2006.02044, 2020 | 24 | 2020 |
| Max-affine regression: Parameter estimation for Gaussian designs A Ghosh, A Pananjady, A Guntuboyina, K Ramchandran IEEE Transactions on Information Theory 68 (3), 1851-1885, 2021 | 23 | 2021 |
| Adaptation in multivariate log-concave density estimation OY Feng, A Guntuboyina, AKH Kim, RJ Samworth | 21 | 2021 |
Bodhisattva SenColumbia University, New YorkVerified email at stat.columbia.edu
