| Randomized sketches for kernels: Fast and optimal nonparametric regression Y Yang, M Pilanci, MJ Wainwright The Annals of Statistics 45 (3), 991-1023, 2017 | 123 | 2017 |
| Communication-efficient distributed statistical inference MI Jordan, JD Lee, Y Yang Journal of the American Statistical Association, 2018 | 103 | 2018 |
| On the computational complexity of high-dimensional Bayesian variable selection Y Yang, MJ Wainwright, MI Jordan The Annals of Statistics 44 (6), 2497-2532, 2016 | 87 | 2016 |
| Bayesian regression tree ensembles that adapt to smoothness and sparsity AR Linero, Y Yang Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2018 | 61 | 2018 |
| Bayesian conditional tensor factorizations for high-dimensional classification Y Yang, DB Dunson Journal of the American Statistical Association 111 (514), 656-669, 2016 | 59 | 2016 |
| Minimax-optimal nonparametric regression in high dimensions Y Yang, ST Tokdar The Annals of Statistics 43 (2), 652-674, 2015 | 55 | 2015 |
| Bayesian fractional posteriors A Bhattacharya, D Pati, Y Yang The Annals of Statistics 47 (1), 39-66, 2019 | 46 | 2019 |
| Bayesian manifold regression Y Yang, DB Dunson The Annals of Statistics 44 (2), 876-905, 2016 | 44 | 2016 |
| On statistical optimality of variational Bayes D Pati, A Bhattacharya, Y Yang International Conference on Artificial Intelligence and Statistics, 1579-1588, 2018 | 40 | 2018 |
| -variational inference with statistical guarantees Y Yang, D Pati, A Bhattacharya Annals of Statistics 48 (2), 886-905, 2020 | 36 | 2020 |
| Joint estimation of quantile planes over arbitrary predictor spaces Y Yang, ST Tokdar Journal of the American Statistical Association 112 (519), 1107-1120, 2017 | 28 | 2017 |
| Bayesian crack detection in ultra high resolution multimodal images of paintings B Cornelis, Y Yang, JT Vogelstein, A Dooms, I Daubechies, D Dunson 2013 18th International Conference on Digital Signal Processing (DSP), 1-8, 2013 | 25 | 2013 |
| Frequentist coverage and sup-norm convergence rate in Gaussian process regression Y Yang, A Bhattacharya, D Pati arXiv preprint arXiv:1708.04753, 2017 | 19 | 2017 |
| Minimax optimal Bayesian aggregation Y Yang, DB Dunson arXiv preprint arXiv:1403.1345, 2014 | 14 | 2014 |
| Sequential Markov Chain Monte Carlo Y Yang, DB Dunson arXiv preprint arXiv:1308.3861, 2013 | 13 | 2013 |
| Hanson-Wright inequality in Hilbert spaces with application to -means clustering for non-Euclidean data X Chen, Y Yang arXiv preprint arXiv:1810.11180, 2018 | 9 | 2018 |
| Bayesian model selection consistency and oracle inequality with intractable marginal likelihood Y Yang, D Pati arXiv preprint arXiv:1701.00311, 2017 | 9 | 2017 |
| A compact neural network for training support vector machines Y Yang, Q He, X Hu Neurocomputing 86, 193-198, 2012 | 9 | 2012 |
| Implicit Regularization via Hadamard Product Over-Parametrization in High-Dimensional Linear Regression P Zhao, Y Yang, QC He arXiv preprint arXiv:1903.09367, 2019 | 8 | 2019 |
| Non-asymptotic theory for nonparametric testing Y Yang, Z Shang, G Cheng arXiv preprint arXiv:1702.01330, 2017 | 8 | 2017 |
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerified email at cs.berkeley.edu
