Rebecca Willett

Orcid: 0000-0002-8109-7582

Affiliations:
  • University of Chicago, IL, USA
  • University of Wisconsin Madison, WI, USA
  • Duke University, Durham, USA


According to our database1, Rebecca Willett authored at least 160 papers between 2002 and 2024.

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Bibliography

2024
Bagging Provides Assumption-free Stability.
J. Mach. Learn. Res., 2024

Stabilizing black-box model selection with the inflated argmax.
CoRR, 2024

Embed and Emulate: Contrastive representations for simulation-based inference.
CoRR, 2024

Nonlinear tomographic reconstruction via nonsmooth optimization.
CoRR, 2024

Building a stable classifier with the inflated argmax.
CoRR, 2024

Data Assimilation with Machine Learning Surrogate Models: A Case Study with FourCastNet.
CoRR, 2024

Residual Connections Harm Self-Supervised Abstract Feature Learning.
CoRR, 2024

Deep Stochastic Mechanics.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Depth Separation in Norm-Bounded Infinite-Width Neural Networks.
Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

Integrating Uncertainty Awareness into Conformalized Quantile Regression.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023
Rotation-Invariant Random Features Provide a Strong Baseline for Machine Learning on 3D Point Clouds.
Trans. Mach. Learn. Res., 2023

Fast, Distribution-free Predictive Inference for Neural Networks with Coverage Guarantees.
CoRR, 2023

Deep Stochastic Mechanics.
CoRR, 2023

Linear Neural Network Layers Promote Learning Single- and Multiple-Index Models.
CoRR, 2023

Reduced-Order Autodifferentiable Ensemble Kalman Filters.
CoRR, 2023

Training neural operators to preserve invariant measures of chaotic attractors.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
Autodifferentiable Ensemble Kalman Filters.
SIAM J. Math. Data Sci., June, 2022

Data-Driven Cloud Clustering via a Rotationally Invariant Autoencoder.
IEEE Trans. Geosci. Remote. Sens., 2022

Functional Linear Regression with Mixed Predictors.
J. Mach. Learn. Res., 2022

Beyond Ensemble Averages: Leveraging Climate Model Ensembles for Subseasonal Forecasting.
CoRR, 2022

Cloud Classification with Unsupervised Deep Learning.
CoRR, 2022

The Role of Linear Layers in Nonlinear Interpolating Networks.
CoRR, 2022

Assessing kernel processing score of harvested corn silage in real-time using image analysis and machine learning.
Comput. Electron. Agric., 2022

Embed and Emulate: Learning to estimate parameters of dynamical systems with uncertainty quantification.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

NURD: Negative-Unlabeled Learning for Online Datacenter Straggler Prediction.
Proceedings of the Fifth Conference on Machine Learning and Systems, 2022

Lazy Estimation of Variable Importance for Large Neural Networks.
Proceedings of the International Conference on Machine Learning, 2022

2021
Deep Equilibrium Architectures for Inverse Problems in Imaging.
IEEE Trans. Computational Imaging, 2021

Model Adaptation for Inverse Problems in Imaging.
IEEE Trans. Computational Imaging, 2021

Tensor Methods for Nonlinear Matrix Completion.
SIAM J. Math. Data Sci., 2021

Context-dependent Networks in Multivariate Time Series: Models, Methods, and Risk Bounds in High Dimensions.
J. Mach. Learn. Res., 2021

Statistically and Computationally Efficient Change Point Localization in Regression Settings.
J. Mach. Learn. Res., 2021

Adaptive Differentially Private Empirical Risk Minimization.
CoRR, 2021

Auto-differentiable Ensemble Kalman Filters.
CoRR, 2021

Prediction in the Presence of Response-Dependent Missing Labels.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2021

Pure Exploration in Kernel and Neural Bandits.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Model Adaptation In Biomedical Image Reconstruction.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

Cloud Clustering Over January 2003 via Scalable Rotationally Invariant Autoencoder.
Proceedings of the 17th IEEE International Conference on eScience, 2021

Localizing Changes in High-Dimensional Regression Models.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Neumann Networks for Linear Inverse Problems in Imaging.
IEEE Trans. Computational Imaging, 2020

Graph Signal Processing: Foundations and Emerging Directions [From the Guest Editors].
IEEE Signal Process. Mag., 2020

Graph-Based Regularization for Regression Problems with Alignment and Highly Correlated Designs.
SIAM J. Math. Data Sci., 2020

Deep Learning Techniques for Inverse Problems in Imaging.
IEEE J. Sel. Areas Inf. Theory, 2020

Guest Editorial.
IEEE J. Sel. Areas Inf. Theory, 2020

Detection and Description of Change in Visual Streams.
CoRR, 2020

Context-dependent self-exciting point processes: models, methods, and risk bounds in high dimensions.
CoRR, 2020

An Optimal Statistical and Computational Framework for Generalized Tensor Estimation.
CoRR, 2020

A Function Space View of Bounded Norm Infinite Width ReLU Nets: The Multivariate Case.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
Network Estimation From Point Process Data.
IEEE Trans. Inf. Theory, 2019

A Data-Dependent Weighted LASSO Under Poisson Noise.
IEEE Trans. Inf. Theory, 2019

Learning High-Dimensional Generalized Linear Autoregressive Models.
IEEE Trans. Inf. Theory, 2019

Online Data Thinning via Multi-Subspace Tracking.
IEEE Trans. Pattern Anal. Mach. Intell., 2019

Neumann Networks for Inverse Problems in Imaging.
CoRR, 2019

Predicting kernel processing score of harvested and processed corn silage via image processing techniques.
Comput. Electron. Agric., 2019

Bilinear Bandits with Low-rank Structure.
Proceedings of the 36th International Conference on Machine Learning, 2019

Learning to Regularize Using Neumann Networks.
Proceedings of the IEEE Data Science Workshop, 2019

Learned Patch-Based Regularization for Inverse Problems in Imaging.
Proceedings of the 8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2019

Estimating Network Structure from Incomplete Event Data.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Graph-based regularization for regression problems with highly-correlated designs.
CoRR, 2018

Missing Data in Sparse Transition Matrix Estimation for Sub-Gaussian Vector Autoregressive Processes.
CoRR, 2018

Graph-Based Regularization for Regression Problems with Highly-Correlated Designs.
Proceedings of the 2018 IEEE Global Conference on Signal and Information Processing, 2018

Sparse Subspace Clustering with Missing and Corrupted Data.
Proceedings of the 2018 IEEE Data Science Workshop, 2018

Sparse Transition Matrix Estimation for Sub-Gaussian Autoregressive Processes with Missing Data.
Proceedings of the 2018 Annual American Control Conference, 2018

2017
Online Learning for Changing Environments using Coin Betting.
CoRR, 2017

Scalable Generalized Linear Bandits: Online Computation and Hashing.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Subspace Clustering via Tangent Cones.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Hawkes Process Modeling of Adverse Drug Reactions with Longitudinal Observational Data.
Proceedings of the Machine Learning for Health Care Conference, 2017

Algebraic Variety Models for High-Rank Matrix Completion.
Proceedings of the 34th International Conference on Machine Learning, 2017

Signal representations in modern signal processing.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Network estimation via poisson autoregressive models.
Proceedings of the 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2017

Proximal-Gradient methods for poisson image reconstruction with BM3D-Based regularization.
Proceedings of the 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2017

Low algebraic dimension matrix completion.
Proceedings of the 55th Annual Allerton Conference on Communication, 2017

Improved Strongly Adaptive Online Learning using Coin Betting.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

On Learning High Dimensional Structured Single Index Models.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Tracking Dynamic Point Processes on Networks.
IEEE Trans. Inf. Theory, 2016

Inference of High-dimensional Autoregressive Generalized Linear Models.
CoRR, 2016

Group-sparse subspace clustering with missing data.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2016

Genomic transcription regulatory element location analysis via poisson weighted lasso.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2016

Inferring high-dimensional poisson autoregressive models.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2016

Atmospheric lidar imaging and poisson inverse problems.
Proceedings of the 2016 IEEE International Conference on Image Processing, 2016

Regret minimization algorithms for single-controller zero-sum stochastic games.
Proceedings of the 55th IEEE Conference on Decision and Control, 2016

2015
Minimax Optimal Rates for Poisson Inverse Problems With Physical Constraints.
IEEE Trans. Inf. Theory, 2015

Online Convex Optimization in Dynamic Environments.
IEEE J. Sel. Top. Signal Process., 2015

Sparse Linear Regression With Missing Data.
CoRR, 2015

Learning Single Index Models in High Dimensions.
CoRR, 2015

Matrix Completion Under Monotonic Single Index Models.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Online learning of neural network structure from spike trains.
Proceedings of the 7th International IEEE/EMBS Conference on Neural Engineering, 2015

2014
Online Markov Decision Processes With Kullback-Leibler Control Cost.
IEEE Trans. Autom. Control., 2014

Sparsity and Structure in Hyperspectral Imaging : Sensing, Reconstruction, and Target Detection.
IEEE Signal Process. Mag., 2014

Reducing Basis Mismatch in Harmonic Signal Recovery via Alternating Convex Search.
IEEE Signal Process. Lett., 2014

Poisson Noise Reduction with Non-local PCA.
J. Math. Imaging Vis., 2014

To e or not to e in poisson image reconstruction.
Proceedings of the 2014 IEEE International Conference on Image Processing, 2014

From minimax value to low-regret algorithms for online Markov decision processes.
Proceedings of the American Control Conference, 2014

2013
Level Set Estimation from Projection Measurements: Performance Guarantees and Fast Computation.
SIAM J. Imaging Sci., 2013

Change-Point Detection for High-Dimensional Time Series With Missing Data.
IEEE J. Sel. Top. Signal Process., 2013

Compressive Coded Aperture Keyed Exposure Imaging with Optical Flow Reconstruction.
CoRR, 2013

Online Optimization in Dynamic Environments.
CoRR, 2013

Relax but stay in control: from value to algorithms for online Markov decision processes.
CoRR, 2013

Dynamical Models and tracking regret in online convex programming.
Proceedings of the 30th International Conference on Machine Learning, 2013

Logarithmic total variation regularization for cross-validation in photon-limited imaging.
Proceedings of the IEEE International Conference on Image Processing, 2013

Foreground and background reconstruction in poisson video.
Proceedings of the IEEE International Conference on Image Processing, 2013

Online logistic regression on manifolds.
Proceedings of the IEEE International Conference on Acoustics, 2013

Dual-scale masks for spatio-temporal compressive imaging.
Proceedings of the IEEE Global Conference on Signal and Information Processing, 2013

Online optimization in parametric dynamic environments.
Proceedings of the 51st Annual Allerton Conference on Communication, 2013

2012
Sequential Anomaly Detection in the Presence of Noise and Limited Feedback.
IEEE Trans. Inf. Theory, 2012

This is SPIRAL-TAP: Sparse Poisson Intensity Reconstruction ALgorithms - Theory and Practice.
IEEE Trans. Image Process., 2012

Oracle Inequalities and Minimax Rates for Nonlocal Means and Related Adaptive Kernel-Based Methods.
SIAM J. Imaging Sci., 2012

Target detection performance bounds in compressive imaging.
EURASIP J. Adv. Signal Process., 2012

Changepoint detection for high-dimensional time series with missing data
CoRR, 2012

Multiscale online tracking of manifolds.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2012

A two-stage denoising filter: The preprocessed Yaroslavsky filter.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2012

The value of multispectral observations in photon-limited quantitative tissue analysis.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2012

2011
Performance Bounds for Expander-Based Compressed Sensing in Poisson Noise.
IEEE Trans. Signal Process., 2011

Oracle inequalities and minimax rates for non-local means and related adaptive kernel-based methods
CoRR, 2011

Smooth sampling trajectories for sparse recovery in MRI.
Proceedings of the 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2011

Short and smooth sampling trajectories for compressed sensing.
Proceedings of the IEEE International Conference on Acoustics, 2011

Time-evolving modeling of social networks.
Proceedings of the IEEE International Conference on Acoustics, 2011

Online anomaly detection with expert system feedback in social networks.
Proceedings of the IEEE International Conference on Acoustics, 2011

Decentralized Online Convex Programming with local information.
Proceedings of the American Control Conference, 2011

2010
Compressed sensing performance bounds under Poisson noise.
IEEE Trans. Signal Process., 2010

Multiscale Photon-Limited Spectral Image Reconstruction.
SIAM J. Imaging Sci., 2010

Sparsity-regularized photon-limited imaging.
Proceedings of the 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2010

Poisson image reconstruction with total variation regularization.
Proceedings of the International Conference on Image Processing, 2010

Hyperspectral target detection from incoherent projections: Nonequiprobable targets and inhomogeneous SNR.
Proceedings of the International Conference on Image Processing, 2010

Gradient projection for linearly constrained convex optimization in sparse signal recovery.
Proceedings of the International Conference on Image Processing, 2010

Hyperspectral target detection from incoherent projections.
Proceedings of the IEEE International Conference on Acoustics, 2010

Fishing in Poisson streams: Focusing on the whales, ignoring the minnows.
Proceedings of the 44th Annual Conference on Information Sciences and Systems, 2010

SPIRAL out of convexity: sparsity-regularized algorithms for photon-limited imaging.
Proceedings of the Computational Imaging VIII, 2010

2009
Hypergraph-Based Anomaly Detection of High-Dimensional Co-Occurrences.
IEEE Trans. Pattern Anal. Mach. Intell., 2009

Sequential anomaly detection in the presence of noise and limited feedback
CoRR, 2009

Performance Bounds for Expander-based Compressed Sensing in the presence of Poisson Noise
CoRR, 2009

Minimax risk for Poisson compressed sensing
CoRR, 2009

Performance bounds on compressed sensing with Poisson noise.
Proceedings of the IEEE International Symposium on Information Theory, 2009

Sequential probability assignment via online convex programming using exponential families.
Proceedings of the IEEE International Symposium on Information Theory, 2009

Image Reconstruction of Multiphoton Microscopy Data.
Proceedings of the 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Boston, MA, USA, June 28, 2009

Compressive coded aperture imaging.
Proceedings of the Computational Imaging VII, 2009

2008
Near-minimax recursive density estimation on the binary hypercube.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Controlling the error in FMRI: Hypothesis testing or set estimation?
Proceedings of the 2008 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2008

Fast disambiguation of superimposed images for increased field of view.
Proceedings of the International Conference on Image Processing, 2008

Compressive coded aperture superresolution image reconstruction.
Proceedings of the IEEE International Conference on Acoustics, 2008

Compressive coded aperture video reconstruction.
Proceedings of the 2008 16th European Signal Processing Conference, 2008

Detection of anomalous meetings in a social network.
Proceedings of the 42nd Annual Conference on Information Sciences and Systems, 2008

2007
Multiscale Poisson Intensity and Density Estimation.
IEEE Trans. Inf. Theory, 2007

Minimax Optimal Level-Set Estimation.
IEEE Trans. Image Process., 2007

Multiscale Intensity Estimation for Multi-Photon Microscopy.
Proceedings of the 2007 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2007

Multiscale Intensity Estimation for Marked Poisson Processes.
Proceedings of the IEEE International Conference on Acoustics, 2007

Multiscale Reconstruction for Photon-Limited Shifted Excitation Raman Spectroscopy.
Proceedings of the IEEE International Conference on Acoustics, 2007

Multiscale reconstruction for computational spectral imaging.
Proceedings of the Computational Imaging V, San Jose, 2007

2005
Faster Rates in Regression via Active Learning.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

Level set estimation via trees [signal processing applications].
Proceedings of the 2005 IEEE International Conference on Acoustics, 2005

2004
Estimating inhomogeneous fields using wireless sensor networks.
IEEE J. Sel. Areas Commun., 2004

Complexity-regularized multiresolution density estimation.
Proceedings of the 2004 IEEE International Symposium on Information Theory, 2004

Adaptive sampling for wireless sensor networks.
Proceedings of the 2004 IEEE International Symposium on Information Theory, 2004

Fast Multiresolution Photon-Limited Image Reconstruction.
Proceedings of the 2004 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2004

Backcasting: adaptive sampling for sensor networks.
Proceedings of the Third International Symposium on Information Processing in Sensor Networks, 2004

Coarse-to-fine manifold learning [image processing example].
Proceedings of the 2004 IEEE International Conference on Acoustics, 2004

Fast, near-optimal, multiresolution estimation of poisson signals and images.
Proceedings of the 2004 12th European Signal Processing Conference, 2004

2003
Platelets: A Multiscale Approach for Recovering Edges and Surfaces in Photon LimitedMedical Imaging.
IEEE Trans. Medical Imaging, 2003

CORT: classification or regression trees.
Proceedings of the 2003 IEEE International Conference on Acoustics, 2003

2002
Platelets for multiscale analysis in photon-limited imaging.
Proceedings of the 2002 International Conference on Image Processing, 2002

Multiresolution nonparametric intensity and density estimation.
Proceedings of the IEEE International Conference on Acoustics, 2002


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