| Trend filtering on graphs YX Wang, J Sharpnack, AJ Smola, RJ Tibshirani Journal of Machine Learning Research 17 (105), 1-41, 2016 | 325 | 2016 |
| SSE-PT: Sequential recommendation via personalized transformer L Wu, S Li, CJ Hsieh, J Sharpnack Proceedings of the 14th ACM conference on recommender systems, 328-337, 2020 | 284 | 2020 |
| A sharp error analysis for the fused lasso, with application to approximate changepoint screening K Lin, JL Sharpnack, A Rinaldo, RJ Tibshirani Advances in neural information processing systems 30, 2017 | 100* | 2017 |
| Sparsistency of the edge lasso over graphs J Sharpnack, A Singh, A Rinaldo Artificial Intelligence and Statistics, 1028-1036, 2012 | 90 | 2012 |
| The DFS fused lasso: Linear-time denoising over general graphs OHM Padilla, J Sharpnack, JG Scott, RJ Tibshirani Journal of Machine Learning Research 18 (176), 1-36, 2018 | 83 | 2018 |
| Changepoint detection over graphs with the spectral scan statistic J Sharpnack, A Singh, A Rinaldo Artificial Intelligence and Statistics, 545-553, 2013 | 79 | 2013 |
| Near-optimal anomaly detection in graphs using lovasz extended scan statistic JL Sharpnack, A Krishnamurthy, A Singh Advances in Neural Information Processing Systems 26, 2013 | 76 | 2013 |
| Psychological stress of bicycling with traffic: examining heart rate variability of bicyclists in natural urban environments DT Fitch, J Sharpnack, SL Handy Transportation research part F: traffic psychology and behaviour 70, 81-97, 2020 | 69* | 2020 |
| An open repository of real-time COVID-19 indicators A Reinhart, L Brooks, M Jahja, A Rumack, J Tang, S Agrawal, W Al Saeed, ... Proceedings of the National Academy of Sciences 118 (51), e2111452118, 2021 | 63 | 2021 |
| Sql-rank: A listwise approach to collaborative ranking L Wu, CJ Hsieh, J Sharpnack International Conference on Machine Learning, 5315-5324, 2018 | 52 | 2018 |
| Detecting anomalous activity on networks with the graph Fourier scan statistic J Sharpnack, A Rinaldo, A Singh IEEE Transactions on Signal Processing 64 (2), 364-379, 2015 | 50 | 2015 |
| Detecting activations over graphs using spanning tree wavelet bases J Sharpnack, A Singh, A Krishnamurthy Artificial intelligence and statistics, 536-544, 2013 | 50 | 2013 |
| Can auxiliary indicators improve COVID-19 forecasting and hotspot prediction? DJ McDonald, J Bien, A Green, AJ Hu, N DeFries, S Hyun, NL Oliveira, ... Proceedings of the National Academy of Sciences 118 (51), e2111453118, 2021 | 46 | 2021 |
| An efficient algorithm for generalized linear bandit: Online stochastic gradient descent and thompson sampling Q Ding, CJ Hsieh, J Sharpnack International Conference on Artificial Intelligence and Statistics, 1585-1593, 2021 | 46 | 2021 |
| Stochastic shared embeddings: Data-driven regularization of embedding layers L Wu, S Li, CJ Hsieh, JL Sharpnack Advances in Neural Information Processing Systems 32, 2019 | 44 | 2019 |
| Adaptive nonparametric regression with the K-nearest neighbour fused lasso OH Madrid Padilla, J Sharpnack, Y Chen, DM Witten Biometrika 107 (2), 293-310, 2020 | 43* | 2020 |
| 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 | 39 | 2017 |
| Exact asymptotics for the scan statistic and fast alternatives J Sharpnack, E Arias-Castro Electronic Journal of Statistics 10 (2), 2641-2684, 2016 | 39 | 2016 |
| Rlsbench: Domain adaptation under relaxed label shift S Garg, N Erickson, J Sharpnack, A Smola, S Balakrishnan, ZC Lipton International Conference on Machine Learning, 10879-10928, 2023 | 37* | 2023 |
| Robust stochastic linear contextual bandits under adversarial attacks Q Ding, CJ Hsieh, J Sharpnack International Conference on Artificial Intelligence and Statistics, 7111-7123, 2022 | 37 | 2022 |
Cho-Jui HsiehUniversity of California, Los AngelesZweryfikowany adres z cs.ucla.edu
