Rebecca Willett

ORCID

Publication Activity (10 Years)

Years Active: 2002-2024
Publications (10 Years): 94

Top Venues

CoRR

AISTATS

SSP

SIAM J. Math. Data Sci.

Publications

Suzanna Parkinson, Greg Ongie, Rebecca Willett, Ohad Shamir, Nathan Srebro
Depth Separation in Norm-Bounded Infinite-Width Neural Networks. COLT (2024)
Raphael Rossellini, Rina Foygel Barber, Rebecca Willett
Integrating Uncertainty Awareness into Conformalized Quantile Regression. AISTATS (2024)
Xiao Zhang, Ruoxi Jiang, William Gao, Rebecca Willett, Michael Maire
Residual Connections Harm Self-Supervised Abstract Feature Learning. CoRR (2024)
Vasileios Charisopoulos, Rebecca Willett
Nonlinear tomographic reconstruction via nonsmooth optimization. CoRR (2024)
Melissa Adrian, Daniel Sanz-Alonso, Rebecca Willett
Data Assimilation with Machine Learning Surrogate Models: A Case Study with FourCastNet. CoRR (2024)
Suzanna Parkinson, Greg Ongie, Rebecca Willett, Ohad Shamir, Nathan Srebro
Depth Separation in Norm-Bounded Infinite-Width Neural Networks. CoRR (2024)
Jake A. Soloff, Rina Foygel Barber, Rebecca Willett
Building a stable classifier with the inflated argmax. CoRR (2024)
Elena Orlova, Aleksei Ustimenko, Ruoxi Jiang, Peter Y. Lu, Rebecca Willett
Deep Stochastic Mechanics. CoRR (2023)
Ruoxi Jiang, Peter Y. Lu, Elena Orlova, Rebecca Willett
Training neural operators to preserve invariant measures of chaotic attractors. CoRR (2023)
Yuming Chen, Daniel Sanz-Alonso, Rebecca Willett
Reduced-Order Autodifferentiable Ensemble Kalman Filters. CoRR (2023)
Suzanna Parkinson, Greg Ongie, Rebecca Willett
Linear Neural Network Layers Promote Learning Single- and Multiple-Index Models. CoRR (2023)
Jake A. Soloff, Rina Foygel Barber, Rebecca Willett
Bagging Provides Assumption-free Stability. CoRR (2023)
Owen Melia, Eric Jonas, Rebecca Willett
Rotation-Invariant Random Features Provide a Strong Baseline for Machine Learning on 3D Point Clouds. CoRR (2023)
Yue Gao, Garvesh Raskutti, Rebecca Willett
Fast, Distribution-free Predictive Inference for Neural Networks with Coverage Guarantees. CoRR (2023)
Ruoxi Jiang, Peter Y. Lu, Elena Orlova, Rebecca Willett
Training neural operators to preserve invariant measures of chaotic attractors. NeurIPS (2023)
Owen Melia, Eric M. Jonas, Rebecca Willett
Rotation-Invariant Random Features Provide a Strong Baseline for Machine Learning on 3D Point Clouds. Trans. Mach. Learn. Res. 2023 (2023)
Ruoxi Jiang, Rebecca Willett
Embed and Emulate: Learning to estimate parameters of dynamical systems with uncertainty quantification. CoRR (2022)
Yi Ding, Avinash Rao, Hyebin Song, Rebecca Willett, Henry Hoffmann
NURD: Negative-Unlabeled Learning for Online Datacenter Straggler Prediction. CoRR (2022)
Yue Gao, Abby Stevens, Rebecca Willett, Garvesh Raskutti
Lazy Estimation of Variable Importance for Large Neural Networks. CoRR (2022)
Ruoxi Jiang, Rebecca Willett
Embed and Emulate: Learning to estimate parameters of dynamical systems with uncertainty quantification. NeurIPS (2022)
Daren Wang, Zifeng Zhao, Yi Yu, Rebecca Willett
Functional Linear Regression with Mixed Predictors. J. Mach. Learn. Res. 23 (2022)
Yue Gao, Abby Stevens, Garvesh Raskutti, Rebecca Willett
Lazy Estimation of Variable Importance for Large Neural Networks. ICML (2022)
Takuya Kurihana, Elisabeth Moyer, Rebecca Willett, Davis Gilton, Ian T. Foster
Data-Driven Cloud Clustering via a Rotationally Invariant Autoencoder. IEEE Trans. Geosci. Remote. Sens. 60 (2022)
Elena Orlova, Haokun Liu, Raphael Rossellini, Benjamin Cash, Rebecca Willett
Beyond Ensemble Averages: Leveraging Climate Model Ensembles for Subseasonal Forecasting. CoRR (2022)
Yi Ding, Avinash Rao, Hyebin Song, Rebecca Willett, Henry Hoffmann
NURD: Negative-Unlabeled Learning for Online Datacenter Straggler Prediction. MLSys (2022)
Greg Ongie, Rebecca Willett
The Role of Linear Layers in Nonlinear Interpolating Networks. CoRR (2022)
Takuya Kurihana, Ian T. Foster, Rebecca Willett, Sydney Jenkins, Kathryn Koenig, Ruby Werman, Ricardo Barros Lourenço, Casper Neo, Elisabeth Moyer
Cloud Classification with Unsupervised Deep Learning. CoRR (2022)
Yuming Chen, Daniel Sanz-Alonso, Rebecca Willett
Autodifferentiable Ensemble Kalman Filters. SIAM J. Math. Data Sci. 4 (2) (2022)
Alessandro Rinaldo, Daren Wang, Qin Wen, Rebecca Willett, Yi Yu
Localizing Changes in High-Dimensional Regression Models. AISTATS (2021)
Xiaoxia Wu, Lingxiao Wang, Irina Cristali, Quanquan Gu, Rebecca Willett
Adaptive Differentially Private Empirical Risk Minimization. CoRR (2021)
Yinglun Zhu, Dongruo Zhou, Ruoxi Jiang, Quanquan Gu, Rebecca Willett, Robert Nowak
Pure Exploration in Kernel and Neural Bandits. NeurIPS (2021)
Takuya Kurihana, Elisabeth Moyer, Rebecca Willett, Davis Gilton, Ian T. Foster
Cloud Clustering Over January 2003 via Scalable Rotationally Invariant Autoencoder. e-Science (2021)
Davis Gilton, Greg Ongie, Rebecca Willett
Model Adaptation In Biomedical Image Reconstruction. ISBI (2021)
Greg Ongie, Daniel L. Pimentel-Alarcón, Laura Balzano, Rebecca Willett, Robert D. Nowak
Tensor Methods for Nonlinear Matrix Completion. SIAM J. Math. Data Sci. 3 (1) (2021)
Hyebin Song, Garvesh Raskutti, Rebecca Willett
Prediction in the presence of response-dependent missing labels. CoRR (2021)
Takuya Kurihana, Elisabeth Moyer, Rebecca Willett, Davis Gilton, Ian T. Foster
Data-driven Cloud Clustering via a Rotationally Invariant Autoencoder. CoRR (2021)
Hyebin Song, Garvesh Raskutti, Rebecca Willett
Prediction in the Presence of Response-Dependent Missing Labels. SSP (2021)
Lili Zheng, Garvesh Raskutti, Rebecca Willett, Benjamin Mark
Context-dependent Networks in Multivariate Time Series: Models, Methods, and Risk Bounds in High Dimensions. J. Mach. Learn. Res. 22 (2021)
Yuming Chen, Daniel Sanz-Alonso, Rebecca Willett
Auto-differentiable Ensemble Kalman Filters. CoRR (2021)
Yinglun Zhu, Dongruo Zhou, Ruoxi Jiang, Quanquan Gu, Rebecca Willett, Robert D. Nowak
Pure Exploration in Kernel and Neural Bandits. CoRR (2021)
Daren Wang, Zifeng Zhao, Kevin Z. Lin, Rebecca Willett
Statistically and Computationally Efficient Change Point Localization in Regression Settings. J. Mach. Learn. Res. 22 (2021)
Davis Gilton, Gregory Ongie, Rebecca Willett
Model Adaptation for Inverse Problems in Imaging. IEEE Trans. Computational Imaging 7 (2021)
Davis Gilton, Gregory Ongie, Rebecca Willett
Deep Equilibrium Architectures for Inverse Problems in Imaging. CoRR (2021)
Davis Gilton, Gregory Ongie, Rebecca Willett
Deep Equilibrium Architectures for Inverse Problems in Imaging. IEEE Trans. Computational Imaging 7 (2021)
Rungang Han, Rebecca Willett, Anru Zhang
An Optimal Statistical and Computational Framework for Generalized Tensor Estimation. CoRR (2020)
Davis Gilton, Ruotian Luo, Rebecca Willett, Greg Shakhnarovich
Detection and Description of Change in Visual Streams. CoRR (2020)
Davis Gilton, Greg Ongie, Rebecca Willett
Neumann Networks for Linear Inverse Problems in Imaging. IEEE Trans. Computational Imaging 6 (2020)
Gregory Ongie, Ajil Jalal, Christopher A. Metzler, Richard G. Baraniuk, Alexandros G. Dimakis, Rebecca Willett
Deep Learning Techniques for Inverse Problems in Imaging. CoRR (2020)
Yuan Li, Benjamin Mark, Garvesh Raskutti, Rebecca Willett, Hyebin Song, David Neiman
Graph-Based Regularization for Regression Problems with Alignment and Highly Correlated Designs. SIAM J. Math. Data Sci. 2 (2) (2020)
Gregory Ongie, Ajil Jalal, Christopher A. Metzler, Richard G. Baraniuk, Alexandros G. Dimakis, Rebecca Willett
Deep Learning Techniques for Inverse Problems in Imaging. IEEE J. Sel. Areas Inf. Theory 1 (1) (2020)
Greg Ongie, Rebecca Willett, Daniel Soudry, Nathan Srebro
A Function Space View of Bounded Norm Infinite Width ReLU Nets: The Multivariate Case. ICLR (2020)
Antonio G. Marques, Negar Kiyavash, José M. F. Moura, Dimitri Van De Ville, Rebecca Willett
Graph Signal Processing: Foundations and Emerging Directions [From the Guest Editors]. IEEE Signal Process. Mag. 37 (6) (2020)
Lili Zheng, Garvesh Raskutti, Rebecca Willett, Benjamin Mark
Context-dependent self-exciting point processes: models, methods, and risk bounds in high dimensions. CoRR (2020)
Davis Gilton, Gregory Ongie, Rebecca Willett
Model Adaptation for Inverse Problems in Imaging. CoRR (2020)
Richard G. Baraniuk, Alex Dimakis, Negar Kiyavash, Sewoong Oh, Rebecca Willett
Guest Editorial. IEEE J. Sel. Areas Inf. Theory 1 (1) (2020)
Benjamin Mark, Garvesh Raskutti, Rebecca Willett
Estimating Network Structure from Incomplete Event Data. AISTATS (2019)
Xin Jiang Hunt, Patricia Reynaud-Bouret, Vincent Rivoirard, Laure Sansonnet, Rebecca Willett
A Data-Dependent Weighted LASSO Under Poisson Noise. IEEE Trans. Inf. Theory 65 (3) (2019)
Davis Gilton, Greg Ongie, Rebecca Willett
Learned Patch-Based Regularization for Inverse Problems in Imaging. CAMSAP (2019)
Kwang-Sung Jun, Rebecca Willett, Stephen J. Wright, Robert D. Nowak
Bilinear Bandits with Low-rank Structure. CoRR (2019)
Kwang-Sung Jun, Rebecca Willett, Stephen J. Wright, Robert D. Nowak
Bilinear Bandits with Low-rank Structure. ICML (2019)
Benjamin Mark, Garvesh Raskutti, Rebecca Willett
Network Estimation From Point Process Data. IEEE Trans. Inf. Theory 65 (5) (2019)
Xin Jiang Hunt, Rebecca Willett
Online Data Thinning via Multi-Subspace Tracking. IEEE Trans. Pattern Anal. Mach. Intell. 41 (5) (2019)
Greg Ongie, Rebecca Willett, Daniel Soudry, Nathan Srebro
A Function Space View of Bounded Norm Infinite Width ReLU Nets: The Multivariate Case. CoRR (2019)
Davis Gilton, Greg Ongie, Rebecca Willett
Learning to Regularize Using Neumann Networks. DSW (2019)
Davis Gilton, Greg Ongie, Rebecca Willett
Neumann Networks for Inverse Problems in Imaging. CoRR (2019)
Amin Jalali, Rebecca Willett
Missing Data in Sparse Transition Matrix Estimation for Sub-Gaussian Vector Autoregressive Processes. CoRR (2018)
Yuan Li, Garvesh Raskutti, Rebecca Willett
Graph-based regularization for regression problems with highly-correlated designs. CoRR (2018)
Benjamin Mark, Garvesh Raskutti, Rebecca Willett
Network Estimation from Point Process Data. CoRR (2018)
Amin Jalali, Rebecca Willett
Sparse Transition Matrix Estimation for Sub-Gaussian Autoregressive Processes with Missing Data. ACC (2018)
Greg Ongie, Laura Balzano, Daniel L. Pimentel-Alarcón, Rebecca Willett, Robert D. Nowak
Tensor Methods for Nonlinear Matrix Completion. CoRR (2018)
Benjamin Mark, Garvesh Raskutti, Rebecca Willett
Estimating Network Structure from Incomplete Event Data. CoRR (2018)
Zachary Charles, Amin Jalali, Rebecca Willett
Sparse Subspace Clustering with Missing and Corrupted Data. DSW (2018)
Yuan Li, Benjamin Mark, Garvesh Raskutti, Rebecca Willett
Graph-Based Regularization for Regression Problems with Highly-Correlated Designs. GlobalSIP (2018)
Rebecca Willett
Signal representations in modern signal processing. ICASSP (2017)
Ravi Ganti, Nikhil S. Rao, Laura Balzano, Rebecca Willett, Robert D. Nowak
On Learning High Dimensional Structured Single Index Models. AAAI (2017)
Benjamin Mark, Garvesh Raskutti, Rebecca Willett
Network estimation via poisson autoregressive models. CAMSAP (2017)
Yujia Bao, Zhaobin Kuang, Peggy L. Peissig, David Page, Rebecca Willett
Hawkes Process Modeling of Adverse Drug Reactions with Longitudinal Observational Data. MLHC (2017)
Greg Ongie, Rebecca Willett, Robert D. Nowak, Laura Balzano
Algebraic Variety Models for High-Rank Matrix Completion. ICML (2017)
Kwang-Sung Jun, Francesco Orabona, Stephen J. Wright, Rebecca Willett
Online Learning for Changing Environments using Coin Betting. CoRR (2017)
Kwang-Sung Jun, Aniruddha Bhargava, Robert D. Nowak, Rebecca Willett
Scalable Generalized Linear Bandits: Online Computation and Hashing. NIPS (2017)
Kwang-Sung Jun, Francesco Orabona, Stephen J. Wright, Rebecca Willett
Improved Strongly Adaptive Online Learning using Coin Betting. AISTATS (2017)
Kwang-Sung Jun, Aniruddha Bhargava, Robert D. Nowak, Rebecca Willett
Scalable Generalized Linear Bandits: Online Computation and Hashing. CoRR (2017)
Willem J. Marais, Rebecca Willett
Proximal-Gradient methods for poisson image reconstruction with BM3D-Based regularization. CAMSAP (2017)
Daniel L. Pimentel-Alarcón, Gregory Ongie, Laura Balzano, Rebecca Willett, Robert D. Nowak
Low algebraic dimension matrix completion. Allerton (2017)
Amin Jalali, Rebecca Willett
Subspace Clustering via Tangent Cones. NIPS (2017)
Xin Jiang Hunt, Rebecca Willett
Online Data Thinning via Multi-Subspace Tracking. CoRR (2016)
Eric C. Hall, Garvesh Raskutti, Rebecca Willett
Inference of High-dimensional Autoregressive Generalized Linear Models. CoRR (2016)
Eric C. Hall, Garvesh Raskutti, Rebecca Willett
Inferring high-dimensional poisson autoregressive models. SSP (2016)
Peng Guan, Maxim Raginsky, Rebecca Willett, Daphney-Stavroula Zois
Regret minimization algorithms for single-controller zero-sum stochastic games. CDC (2016)
Willem J. Marais, Robert E. Holz, Yu Hen Hu, Rebecca Willett
Atmospheric lidar imaging and poisson inverse problems. ICIP (2016)
Kwang-Sung Jun, Francesco Orabona, Rebecca Willett, Stephen J. Wright
Improved Strongly Adaptive Online Learning using Coin Betting. CoRR (2016)
Daniel L. Pimentel-Alarcón, Laura Balzano, Roummel F. Marcia, Robert D. Nowak, Rebecca Willett
Group-sparse subspace clustering with missing data. SSP (2016)
Xin Jiang Hunt, Patricia Reynaud-Bouret, Vincent Rivoirard, Laure Sansonnet, Rebecca Willett
Genomic transcription regulatory element location analysis via poisson weighted lasso. SSP (2016)
Nikhil S. Rao, Ravi Ganti, Laura Balzano, Rebecca Willett, Robert D. Nowak
On Learning High Dimensional Structured Single Index Models. CoRR (2016)
Ravi Sastry Ganti Mahapatruni, Laura Balzano, Rebecca Willett
Matrix Completion Under Monotonic Single Index Models. NIPS (2015)
Ravi Ganti, Laura Balzano, Rebecca Willett
Matrix Completion Under Monotonic Single Index Models. CoRR (2015)
Xin Jiang Hunt, Garvesh Raskutti, Rebecca Willett
Minimax Optimal Rates for Poisson Inverse Problems With Physical Constraints. IEEE Trans. Inf. Theory 61 (8) (2015)
Xin Jiang Hunt, Patricia Reynaud-Bouret, Vincent Rivoirard, Laure Sansonnet, Rebecca Willett
A data-dependent weighted LASSO under Poisson noise. CoRR (2015)
Peng Guan, Maxim Raginsky, Rebecca Willett
Online Markov decision processes with Kullback-Leibler control cost. CoRR (2014)
Peng Guan, Maxim Raginsky, Rebecca Willett
From minimax value to low-regret algorithms for online Markov decision processes. ACC (2014)

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Publication Activity (10 Years)

Top Topics

Top Venues

Rebecca Willett