| Total Variation Classes Beyond 1d: Minimax Rates, and the Limitations of Linear Smoothers V Sadhanala, YX Wang, R Tibshirani Advances in Neural Information Processing Systems 29, 3513--3521, 2016 | 75 | 2016 |
| Additive models with trend filtering V Sadhanala, RJ Tibshirani The Annals of Statistics 47 (6), 3032-3068, 2019 | 60 | 2019 |
| Parallel and distributed block-coordinate frank-wolfe algorithms YX Wang, V Sadhanala, W Dai, W Neiswanger, S Sra, E Xing International Conference on Machine Learning, 1548-1557, 2016 | 56* | 2016 |
| Graph sparsification approaches for laplacian smoothing V Sadhanala, YX Wang, R Tibshirani Artificial Intelligence and Statistics, 1250-1259, 2016 | 49 | 2016 |
| Higher-order total variation classes on grids: Minimax theory and trend filtering methods V Sadhanala, YX Wang, JL Sharpnack, RJ Tibshirani Advances in Neural Information Processing Systems 30, 2017 | 31 | 2017 |
| Scheduling of dataflow models within the reconfigurable video coding framework J Boutellier, V Sadhanala, C Lucarz, P Brisk, M Mattavelli 2008 IEEE Workshop on Signal Processing Systems, 182-187, 2008 | 21 | 2008 |
| A higher-order kolmogorov-smirnov test V Sadhanala, YX Wang, A Ramdas, RJ Tibshirani The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 16 | 2019 |
| Multivariate Trend Filtering for Lattice Data V Sadhanala, YX Wang, A Hu, R Tibshirani arXiv, 2021 | 9 | 2021 |
| glmgen: Fast generalized lasso solver T Arnold, V Sadhanala, RJ Tibshirani | 7 | 2014 |
| EmbedDistill: A Geometric Knowledge Distillation for Information Retrieval S Kim, AS Rawat, M Zaheer, S Jayasumana, V Sadhanala, W Jitkrittum, ... arXiv preprint arXiv:2301.12005, 2023 | 4 | 2023 |
| Nonparametric methods with total variation type regularization V Sadhanala National Institutes of Health, 2019 | 2 | 2019 |
| Supplement to “Additive Models with Trend Filtering.” V Sadhanala, RJ Tibshirani DOI, 2019 | 1 | 2019 |
| Exponential Family Trend Filtering on Lattices V Sadhanala, R Bassett, J Sharpnack, DJ McDonald arXiv preprint arXiv:2209.09175, 2022 | | 2022 |
| CMU-ML-19-104 Nonparametric Methods with Total Variation Type Regularization V Sadhanala | | |
| Supplement to “A Higher-Order Kolmogorov-Smirnov Test” V Sadhanala, YX Wang, A Ramdas, RJ Tibshirani | | |
| Wireless Mesh Network design by Optimization of Spectral Properties and Max-k-Cut V Sadhanala | | |
| Supplement to “Higher-Order Total Variation Classes on Grids: Minimax Theory and Trend Filtering Methods” V Sadhanala, YX Wang, J Sharpnack, RJ Tibshirani | | |
| Supplement to “Total Variation Classes Beyond 1d: Minimax Rates, and the Limitations of Linear Smoothers” V Sadhanala, YX Wang, RJ Tibshirani | | |
| Supplement to “Graph Sparsification Approaches for Laplacian Smoothing” V Sadhanala, YX Wang, RJ Tibshirani | | |
Ryan TibshiraniProfessor of StatisticsVerifierad e-postadress på berkeley.edu
