NSF HDR - Publications

2021

Axel Böhm, and Stephen J. Wright. "Variable smoothing for weakly convex composite functions." Journal of Optimization Theory and Applications 188, no. 3 (2021): 628-649. [link]
Sijie He, Xinyan Li, Timothy DelSole, Pradeep Ravikumar, and Arindam Banerjee. "Sub-seasonal climate forecasting via machine learning: Challenges, analysis, and advances." AAAI Conference on Artificial Intelligence, 2021. [link]
Alessandro Rinaldo, Daren Wang, Qin Wen, Rebecca Willett, and Yi Yu. "Localizing changes in high-dimensional regression models." In International Conference on Artificial Intelligence and Statistics, pp. 2089-2097. PMLR, 2021. [link]
Vishwak Srinivasan, Justin Khim, Arindam Banerjee, and Pradeep Ravikumar. "Subseasonal Climate Prediction in the Western US using Bayesian Spatial Models." Conference on Uncertainty in Artificial Intelligence, 2021.
Abby Stevens, Rebecca Willett, Antonios Mamalakis, Efi Foufoula-Georgiou, Alejandro Tejedor, James T. Randerson, Padhraic Smyth, and Stephen Wright. "Graph-guided regularized regression of Pacific Ocean climate variables to increase predictive skill of southwestern US winter precipitation." Journal of Climate 34, no. 2 (2021): 737-754. [link]
Yue Xie, and Stephen J. Wright. "Complexity of proximal augmented Lagrangian for nonconvex optimization with nonlinear equality constraints." Journal of Scientific Computing 86, no. 3 (2021): 1-30. [link]
Aydin Buluc, Tamara G. Kolda, Stefan M. Wild, Mihai Anitescu, Anthony DeGennaro, John Jakeman, Chandrika Kamath et al. "Randomized algorithms for scientific computing (RASC)." arXiv preprint arXiv:2104.11079, 2021. [link]
Yuming Chen, Daniel Sanz-Alonso, and Rebecca Willett. "Auto-differentiable Ensemble Kalman Filters." arXiv preprint arXiv:2107.07687, 2021. [link]
Zhiyan Ding, Shi Chen, Qin Li, and Stephen Wright. "Overparameterization of deep ResNet: zero loss and mean-field analysis." arXiv preprint arXiv:2105.14417, 2021. [link]
Takuya Kurihana, Elisabeth Moyer, Rebecca Willett, Davis Gilton, and Ian Foster. "Data-driven Cloud Clustering via a Rotationally Invariant Autoencoder." arXiv preprint arXiv:2103.04885, 2021. [link]
Chaobing Song, Stephen J. Wright, and Jelena Diakonikolas. "Variance Reduction via Primal-Dual Accelerated Dual Averaging for Nonsmooth Convex Finite-Sums." arXiv preprint arXiv:2102.13643, 2021. [link]
Hyebin Song, Garvesh Raskutti, and Rebecca Willett. "Prediction in the presence of response-dependent missing labels." arXiv preprint arXiv:2103.13555, 2021. [link]
Yue Xie, and Stephen J. Wright. "Complexity of Projected Newton Methods for Bound-constrained Optimization." arXiv preprint arXiv:2103.15989, 2021. [link]
Yinglun Zhu, Dongruo Zhou, Ruoxi Jiang, Quanquan Gu, Rebecca Willett, and Robert Nowak. "Pure Exploration in Kernel and Neural Bandits." arXiv preprint arXiv:2106.12034, 2021. [link]

2020

Robert Giaquinto and Arindam Banerjee. "Gradient Boosted Normalizing Flows." Advances in Neural Information Processing Systems 33, 2020. [link]
Blake Mason, Lalit Jain, Ardhendu Tripathy, and Robert Nowak. "Finding All epsilon-Good Arms in Stochastic Bandits." Advances in Neural Information Processing Systems 33, 2020. [link]
Gregory Ongie, Ajil Jalal, Christopher A. Metzler, Richard G. Baraniuk, Alexandros G. Dimakis, and Rebecca Willett. "Deep learning techniques for inverse problems in imaging." IEEE Journal on Selected Areas in Information Theory 1, no. 1 (2020): 39-56. [link]
Davis Gilton, Ruotian Luo, Rebecca Willett, and Greg Shakhnarovich. "Detection and description of change in visual streams." arXiv preprint arXiv:2003.12633, 2020. [link]
Rungang Han, Rebecca Willett, and Anru Zhang. "An optimal statistical and computational framework for generalized tensor estimation." arXiv preprint arXiv:2002.11255, 2020. [link]
Daren Wang, Zifeng Zhao, Yi Yu, and Rebecca Willett. "Functional Linear Regression with Mixed Predictors." arXiv preprint arXiv:2012.00460, 2020. [link]
Yinglun Zhu and Robert Nowak. "On Regret with Multiple Best Arms." arXiv preprint arXiv:2006.14785, 2020. [link]

2019

Davis Gilton, Greg Ongie, and Rebecca Willett. "Neumann networks for linear inverse problems in imaging." IEEE Transactions on Computational Imaging 6 (2019): 328-343. [link]
Davis Gilton, Greg Ongie, and Rebecca Willett. "Learned patch-based regularization for inverse problems in imaging." 2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP). [link]
Daren Wang, Kevin Lin, and Rebecca Willett. "Statistically and computationally efficient change point localization in regression settings." arXiv preprint arXiv:1906.11364, 2019. [link]
Daren Wang, Yi Yu, Alessandro Rinaldo, and Rebecca Willett. "Localizing changes in high-dimensional vector autoregressive processes." arXiv preprint arXiv:1909.06359, 2019. [link]