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Rebecca Willett
Rebecca M. Willett
Person information
- affiliation: University of Chicago, IL, USA
- affiliation: University of Wisconsin Madison, WI, USA
- affiliation: Duke University, Durham, USA
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2020 – today
- 2024
- [j42]Jake A. Soloff, Rina Foygel Barber, Rebecca Willett:
Bagging Provides Assumption-free Stability. J. Mach. Learn. Res. 25: 131:1-131:35 (2024) - [c87]Raphael Rossellini, Rina Foygel Barber, Rebecca Willett:
Integrating Uncertainty Awareness into Conformalized Quantile Regression. AISTATS 2024: 1540-1548 - [c86]Suzanna Parkinson, Greg Ongie, Rebecca Willett, Ohad Shamir, Nathan Srebro:
Depth Separation in Norm-Bounded Infinite-Width Neural Networks. COLT 2024: 4082-4114 - [c85]Elena Orlova, Aleksei Ustimenko, Ruoxi Jiang, Peter Y. Lu, Rebecca Willett:
Deep Stochastic Mechanics. ICML 2024 - [i66]Suzanna Parkinson, Greg Ongie, Rebecca Willett, Ohad Shamir, Nathan Srebro:
Depth Separation in Norm-Bounded Infinite-Width Neural Networks. CoRR abs/2402.08808 (2024) - [i65]Xiao Zhang, Ruoxi Jiang, William Gao, Rebecca Willett, Michael Maire:
Residual Connections Harm Self-Supervised Abstract Feature Learning. CoRR abs/2404.10947 (2024) - [i64]Melissa Adrian, Daniel Sanz-Alonso, Rebecca Willett:
Data Assimilation with Machine Learning Surrogate Models: A Case Study with FourCastNet. CoRR abs/2405.13180 (2024) - [i63]Jake A. Soloff, Rina Foygel Barber, Rebecca Willett:
Building a stable classifier with the inflated argmax. CoRR abs/2405.14064 (2024) - [i62]Vasileios Charisopoulos, Rebecca Willett:
Nonlinear tomographic reconstruction via nonsmooth optimization. CoRR abs/2407.12984 (2024) - [i61]Ruoxi Jiang, Peter Y. Lu, Rebecca Willett:
Embed and Emulate: Contrastive representations for simulation-based inference. CoRR abs/2409.18402 (2024) - [i60]Melissa Adrian, Jake A. Soloff, Rebecca Willett:
Stabilizing black-box model selection with the inflated argmax. CoRR abs/2410.18268 (2024) - [i59]Xiao Zhang, Ruoxi Jiang, Rebecca Willett, Michael Maire:
Nested Diffusion Models Using Hierarchical Latent Priors. CoRR abs/2412.05984 (2024) - 2023
- [j41]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) - [c84]Ruoxi Jiang, Peter Y. Lu, Elena Orlova, Rebecca Willett:
Training neural operators to preserve invariant measures of chaotic attractors. NeurIPS 2023 - [i58]Yuming Chen, Daniel Sanz-Alonso, Rebecca Willett:
Reduced-Order Autodifferentiable Ensemble Kalman Filters. CoRR abs/2301.11961 (2023) - [i57]Jake A. Soloff, Rina Foygel Barber, Rebecca Willett:
Bagging Provides Assumption-free Stability. CoRR abs/2301.12600 (2023) - [i56]Suzanna Parkinson, Greg Ongie, Rebecca Willett:
Linear Neural Network Layers Promote Learning Single- and Multiple-Index Models. CoRR abs/2305.15598 (2023) - [i55]Elena Orlova, Aleksei Ustimenko, Ruoxi Jiang, Peter Y. Lu, Rebecca Willett:
Deep Stochastic Mechanics. CoRR abs/2305.19685 (2023) - [i54]Ruoxi Jiang, Peter Y. Lu, Elena Orlova, Rebecca Willett:
Training neural operators to preserve invariant measures of chaotic attractors. CoRR abs/2306.01187 (2023) - [i53]Yue Gao, Garvesh Raskutti, Rebecca Willett:
Fast, Distribution-free Predictive Inference for Neural Networks with Coverage Guarantees. CoRR abs/2306.06582 (2023) - [i52]Owen Melia, Eric M. Jonas, Rebecca Willett:
Rotation-Invariant Random Features Provide a Strong Baseline for Machine Learning on 3D Point Clouds. CoRR abs/2308.06271 (2023) - 2022
- [j40]Eduardo M. C. Rocha, Jessica L. Drewry, Rebecca M. Willett, Brian D. Luck
:
Assessing kernel processing score of harvested corn silage in real-time using image analysis and machine learning. Comput. Electron. Agric. 203: 107415 (2022) - [j39]Daren Wang, Zifeng Zhao, Yi Yu, Rebecca Willett:
Functional Linear Regression with Mixed Predictors. J. Mach. Learn. Res. 23: 266:1-266:94 (2022) - [j38]Yuming Chen
, Daniel Sanz-Alonso, Rebecca Willett:
Autodifferentiable Ensemble Kalman Filters. SIAM J. Math. Data Sci. 4(2): 801-833 (2022) - [j37]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: 1-25 (2022) - [c83]Yue Gao
, Abby Stevens, Garvesh Raskutti, Rebecca Willett:
Lazy Estimation of Variable Importance for Large Neural Networks. ICML 2022: 7122-7143 - [c82]Yi Ding, Avinash Rao, Hyebin Song, Rebecca Willett, Henry Hoffmann:
NURD: Negative-Unlabeled Learning for Online Datacenter Straggler Prediction. MLSys 2022 - [c81]Ruoxi Jiang, Rebecca Willett:
Embed and Emulate: Learning to estimate parameters of dynamical systems with uncertainty quantification. NeurIPS 2022 - [i51]Greg Ongie, Rebecca Willett:
The Role of Linear Layers in Nonlinear Interpolating Networks. CoRR abs/2202.00856 (2022) - [i50]Yi Ding, Avinash Rao, Hyebin Song, Rebecca Willett, Henry Hoffmann:
NURD: Negative-Unlabeled Learning for Online Datacenter Straggler Prediction. CoRR abs/2203.08339 (2022) - [i49]Yue Gao, Abby Stevens, Rebecca Willett, Garvesh Raskutti:
Lazy Estimation of Variable Importance for Large Neural Networks. CoRR abs/2207.09097 (2022) - [i48]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 abs/2209.15585 (2022) - [i47]Ruoxi Jiang, Rebecca Willett:
Embed and Emulate: Learning to estimate parameters of dynamical systems with uncertainty quantification. CoRR abs/2211.01554 (2022) - [i46]Elena Orlova, Haokun Liu, Raphael Rossellini, Benjamin Cash, Rebecca Willett:
Beyond Ensemble Averages: Leveraging Climate Model Ensembles for Subseasonal Forecasting. CoRR abs/2211.15856 (2022) - 2021
- [j36]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: 216:1-216:88 (2021) - [j35]Daren Wang, Zifeng Zhao, Kevin Z. Lin, Rebecca Willett:
Statistically and Computationally Efficient Change Point Localization in Regression Settings. J. Mach. Learn. Res. 22: 248:1-248:46 (2021) - [j34]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): 253-279 (2021) - [j33]Davis Gilton
, Gregory Ongie
, Rebecca Willett
:
Model Adaptation for Inverse Problems in Imaging. IEEE Trans. Computational Imaging 7: 661-674 (2021) - [j32]Davis Gilton
, Gregory Ongie
, Rebecca Willett
:
Deep Equilibrium Architectures for Inverse Problems in Imaging. IEEE Trans. Computational Imaging 7: 1123-1133 (2021) - [c80]Alessandro Rinaldo, Daren Wang, Qin Wen, Rebecca Willett, Yi Yu:
Localizing Changes in High-Dimensional Regression Models. AISTATS 2021: 2089-2097 - [c79]Takuya Kurihana, Elisabeth Moyer, Rebecca Willett, Davis Gilton, Ian T. Foster:
Cloud Clustering Over January 2003 via Scalable Rotationally Invariant Autoencoder. e-Science 2021: 253-254 - [c78]Davis Gilton, Greg Ongie
, Rebecca Willett:
Model Adaptation In Biomedical Image Reconstruction. ISBI 2021: 1223-1226 - [c77]Yinglun Zhu, Dongruo Zhou
, Ruoxi Jiang, Quanquan Gu, Rebecca Willett, Robert Nowak:
Pure Exploration in Kernel and Neural Bandits. NeurIPS 2021: 11618-11630 - [c76]Hyebin Song, Garvesh Raskutti, Rebecca Willett:
Prediction in the Presence of Response-Dependent Missing Labels. SSP 2021: 451-455 - [i45]Davis Gilton, Gregory Ongie, Rebecca Willett:
Deep Equilibrium Architectures for Inverse Problems in Imaging. CoRR abs/2102.07944 (2021) - [i44]Takuya Kurihana, Elisabeth Moyer, Rebecca Willett, Davis Gilton, Ian T. Foster:
Data-driven Cloud Clustering via a Rotationally Invariant Autoencoder. CoRR abs/2103.04885 (2021) - [i43]Hyebin Song, Garvesh Raskutti, Rebecca Willett:
Prediction in the presence of response-dependent missing labels. CoRR abs/2103.13555 (2021) - [i42]Yinglun Zhu, Dongruo Zhou, Ruoxi Jiang, Quanquan Gu, Rebecca Willett, Robert D. Nowak:
Pure Exploration in Kernel and Neural Bandits. CoRR abs/2106.12034 (2021) - [i41]Yuming Chen, Daniel Sanz-Alonso, Rebecca Willett:
Auto-differentiable Ensemble Kalman Filters. CoRR abs/2107.07687 (2021) - [i40]Xiaoxia Wu, Lingxiao Wang, Irina Cristali, Quanquan Gu, Rebecca Willett:
Adaptive Differentially Private Empirical Risk Minimization. CoRR abs/2110.07435 (2021) - 2020
- [j31]Richard G. Baraniuk, Alex Dimakis
, Negar Kiyavash, Sewoong Oh, Rebecca Willett:
Guest Editorial. IEEE J. Sel. Areas Inf. Theory 1(1): 4 (2020) - [j30]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): 39-56 (2020) - [j29]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): 480-504 (2020) - [j28]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): 11-13 (2020) - [j27]Davis Gilton
, Greg Ongie
, Rebecca Willett
:
Neumann Networks for Linear Inverse Problems in Imaging. IEEE Trans. Computational Imaging 6: 328-343 (2020) - [c75]Greg Ongie, Rebecca Willett, Daniel Soudry, Nathan Srebro:
A Function Space View of Bounded Norm Infinite Width ReLU Nets: The Multivariate Case. ICLR 2020 - [i39]Rungang Han, Rebecca Willett, Anru Zhang:
An Optimal Statistical and Computational Framework for Generalized Tensor Estimation. CoRR abs/2002.11255 (2020) - [i38]Lili Zheng, Garvesh Raskutti, Rebecca Willett, Benjamin Mark:
Context-dependent self-exciting point processes: models, methods, and risk bounds in high dimensions. CoRR abs/2003.07429 (2020) - [i37]Davis Gilton, Ruotian Luo, Rebecca Willett, Greg Shakhnarovich:
Detection and Description of Change in Visual Streams. CoRR abs/2003.12633 (2020) - [i36]Gregory Ongie, Ajil Jalal, Christopher A. Metzler, Richard G. Baraniuk, Alexandros G. Dimakis, Rebecca Willett:
Deep Learning Techniques for Inverse Problems in Imaging. CoRR abs/2005.06001 (2020) - [i35]Davis Gilton, Gregory Ongie, Rebecca Willett:
Model Adaptation for Inverse Problems in Imaging. CoRR abs/2012.00139 (2020)
2010 – 2019
- 2019
- [j26]Jessica L. Drewry, Brian D. Luck
, Rebecca M. Willett, Eduardo M. C. Rocha
, Joshua D. Harmon:
Predicting kernel processing score of harvested and processed corn silage via image processing techniques. Comput. Electron. Agric. 160: 144-152 (2019) - [j25]Xin Jiang Hunt
, Rebecca Willett
:
Online Data Thinning via Multi-Subspace Tracking. IEEE Trans. Pattern Anal. Mach. Intell. 41(5): 1173-1187 (2019) - [j24]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): 1589-1613 (2019) - [j23]Eric C. Hall
, Garvesh Raskutti, Rebecca M. Willett
:
Learning High-Dimensional Generalized Linear Autoregressive Models. IEEE Trans. Inf. Theory 65(4): 2401-2422 (2019) - [j22]Benjamin Mark
, Garvesh Raskutti, Rebecca Willett
:
Network Estimation From Point Process Data. IEEE Trans. Inf. Theory 65(5): 2953-2975 (2019) - [c74]Benjamin Mark, Garvesh Raskutti, Rebecca Willett:
Estimating Network Structure from Incomplete Event Data. AISTATS 2019: 2535-2544 - [c73]Davis Gilton, Greg Ongie
, Rebecca Willett:
Learned Patch-Based Regularization for Inverse Problems in Imaging. CAMSAP 2019: 211-215 - [c72]Davis Gilton, Greg Ongie
, Rebecca Willett:
Learning to Regularize Using Neumann Networks. DSW 2019: 201-207 - [c71]Kwang-Sung Jun, Rebecca Willett, Stephen J. Wright, Robert D. Nowak:
Bilinear Bandits with Low-rank Structure. ICML 2019: 3163-3172 - [i34]Kwang-Sung Jun, Rebecca Willett, Stephen J. Wright, Robert D. Nowak:
Bilinear Bandits with Low-rank Structure. CoRR abs/1901.02470 (2019) - [i33]Davis Gilton, Greg Ongie, Rebecca Willett:
Neumann Networks for Inverse Problems in Imaging. CoRR abs/1901.03707 (2019) - [i32]Greg Ongie, Rebecca Willett, Daniel Soudry, Nathan Srebro:
A Function Space View of Bounded Norm Infinite Width ReLU Nets: The Multivariate Case. CoRR abs/1910.01635 (2019) - 2018
- [c70]Amin Jalali, Rebecca Willett:
Sparse Transition Matrix Estimation for Sub-Gaussian Autoregressive Processes with Missing Data. ACC 2018: 1881-1886 - [c69]Zachary Charles, Amin Jalali, Rebecca Willett:
Sparse Subspace Clustering with Missing and Corrupted Data. DSW 2018: 180-184 - [c68]Yuan Li, Benjamin Mark, Garvesh Raskutti, Rebecca Willett:
Graph-Based Regularization for Regression Problems with Highly-Correlated Designs. GlobalSIP 2018: 740-742 - [i31]Benjamin Mark, Garvesh Raskutti, Rebecca Willett:
Network Estimation from Point Process Data. CoRR abs/1802.04838 (2018) - [i30]Amin Jalali, Rebecca Willett:
Missing Data in Sparse Transition Matrix Estimation for Sub-Gaussian Vector Autoregressive Processes. CoRR abs/1802.09511 (2018) - [i29]Yuan Li, Garvesh Raskutti, Rebecca Willett:
Graph-based regularization for regression problems with highly-correlated designs. CoRR abs/1803.07658 (2018) - [i28]Greg Ongie, Laura Balzano, Daniel L. Pimentel-Alarcón, Rebecca Willett, Robert D. Nowak:
Tensor Methods for Nonlinear Matrix Completion. CoRR abs/1804.10266 (2018) - [i27]Benjamin Mark, Garvesh Raskutti, Rebecca Willett:
Estimating Network Structure from Incomplete Event Data. CoRR abs/1811.02979 (2018) - 2017
- [c67]Ravi Ganti, Nikhil Rao, Laura Balzano, Rebecca Willett, Robert D. Nowak:
On Learning High Dimensional Structured Single Index Models. AAAI 2017: 1898-1904 - [c66]Kwang-Sung Jun, Francesco Orabona, Stephen J. Wright, Rebecca Willett:
Improved Strongly Adaptive Online Learning using Coin Betting. AISTATS 2017: 943-951 - [c65]Daniel L. Pimentel-Alarcón, Gregory Ongie
, Laura Balzano
, Rebecca Willett, Robert D. Nowak:
Low algebraic dimension matrix completion. Allerton 2017: 790-797 - [c64]Willem J. Marais, Rebecca Willett:
Proximal-Gradient methods for poisson image reconstruction with BM3D-Based regularization. CAMSAP 2017: 1-5 - [c63]Benjamin Mark, Garvesh Raskutti, Rebecca Willett:
Network estimation via poisson autoregressive models. CAMSAP 2017: 1-5 - [c62]Rebecca Willett:
Signal representations in modern signal processing. ICASSP 2017: 6453-6457 - [c61]Greg Ongie, Rebecca Willett, Robert D. Nowak, Laura Balzano:
Algebraic Variety Models for High-Rank Matrix Completion. ICML 2017: 2691-2700 - [c60]Yujia Bao, Zhaobin Kuang, Peggy L. Peissig, David Page, Rebecca Willett:
Hawkes Process Modeling of Adverse Drug Reactions with Longitudinal Observational Data. MLHC 2017: 177-190 - [c59]Kwang-Sung Jun, Aniruddha Bhargava, Robert D. Nowak, Rebecca Willett:
Scalable Generalized Linear Bandits: Online Computation and Hashing. NIPS 2017: 99-109 - [c58]Amin Jalali, Rebecca Willett:
Subspace Clustering via Tangent Cones. NIPS 2017: 6744-6753 - [i26]Kwang-Sung Jun, Aniruddha Bhargava, Robert D. Nowak, Rebecca Willett:
Scalable Generalized Linear Bandits: Online Computation and Hashing. CoRR abs/1706.00136 (2017) - [i25]Kwang-Sung Jun, Francesco Orabona, Stephen J. Wright, Rebecca Willett:
Online Learning for Changing Environments using Coin Betting. CoRR abs/1711.02545 (2017) - 2016
- [j21]Eric C. Hall
, Rebecca M. Willett:
Tracking Dynamic Point Processes on Networks. IEEE Trans. Inf. Theory 62(7): 4327-4346 (2016) - [c57]Peng Guan, Maxim Raginsky, Rebecca Willett, Daphney-Stavroula Zois
:
Regret minimization algorithms for single-controller zero-sum stochastic games. CDC 2016: 7075-7080 - [c56]Willem J. Marais, Robert E. Holz, Yu Hen Hu, Rebecca Willett
:
Atmospheric lidar imaging and poisson inverse problems. ICIP 2016: 983-987 - [c55]Eric C. Hall, Garvesh Raskutti, Rebecca Willett
:
Inferring high-dimensional poisson autoregressive models. SSP 2016: 1-5 - [c54]Xin Jiang Hunt, Patricia Reynaud-Bouret, Vincent Rivoirard, Laure Sansonnet, Rebecca Willett
:
Genomic transcription regulatory element location analysis via poisson weighted lasso. SSP 2016: 1-5 - [c53]Daniel L. Pimentel-Alarcón, Laura Balzano
, Roummel F. Marcia, Robert D. Nowak, Rebecca Willett:
Group-sparse subspace clustering with missing data. SSP 2016: 1-5 - [i24]Nikhil Rao, Ravi Ganti, Laura Balzano, Rebecca Willett, Robert D. Nowak:
On Learning High Dimensional Structured Single Index Models. CoRR abs/1603.03980 (2016) - [i23]Eric C. Hall, Garvesh Raskutti, Rebecca Willett:
Inference of High-dimensional Autoregressive Generalized Linear Models. CoRR abs/1605.02693 (2016) - [i22]Xin Jiang Hunt, Rebecca Willett:
Online Data Thinning via Multi-Subspace Tracking. CoRR abs/1609.03544 (2016) - [i21]Kwang-Sung Jun, Francesco Orabona, Rebecca Willett, Stephen J. Wright:
Improved Strongly Adaptive Online Learning using Coin Betting. CoRR abs/1610.04578 (2016) - 2015
- [j20]Eric C. Hall, Rebecca M. Willett:
Online Convex Optimization in Dynamic Environments. IEEE J. Sel. Top. Signal Process. 9(4): 647-662 (2015) - [j19]Xin Jiang Hunt, Garvesh Raskutti, Rebecca Willett:
Minimax Optimal Rates for Poisson Inverse Problems With Physical Constraints. IEEE Trans. Inf. Theory 61(8): 4458-4474 (2015) - [c52]Eric C. Hall, Rebecca M. Willett
:
Online learning of neural network structure from spike trains. NER 2015: 930-933 - [c51]Ravi Sastry Ganti Mahapatruni, Laura Balzano, Rebecca Willett:
Matrix Completion Under Monotonic Single Index Models. NIPS 2015: 1873-1881 - [i20]Ravi Ganti, Rebecca M. Willett:
Sparse Linear Regression With Missing Data. CoRR abs/1503.08348 (2015) - [i19]Ravi Ganti, Nikhil Rao, Rebecca M. Willett, Robert D. Nowak:
Learning Single Index Models in High Dimensions. CoRR abs/1506.08910 (2015) - [i18]Xin Jiang Hunt, Patricia Reynaud-Bouret, Vincent Rivoirard, Laure Sansonnet, Rebecca Willett:
A data-dependent weighted LASSO under Poisson noise. CoRR abs/1509.08892 (2015) - [i17]Ravi Ganti, Laura Balzano, Rebecca Willett:
Matrix Completion Under Monotonic Single Index Models. CoRR abs/1512.08787 (2015) - 2014
- [j18]Joseph Salmon, Zachary T. Harmany, Charles-Alban Deledalle, Rebecca Willett
:
Poisson Noise Reduction with Non-local PCA. J. Math. Imaging Vis. 48(2): 279-294 (2014) - [j17]Jonathan M. Nichols, Albert K. Oh, Rebecca M. Willett
:
Reducing Basis Mismatch in Harmonic Signal Recovery via Alternating Convex Search. IEEE Signal Process. Lett. 21(8): 1007-1011 (2014) - [j16]Rebecca M. Willett
, Marco F. Duarte, Mark A. Davenport, Richard G. Baraniuk:
Sparsity and Structure in Hyperspectral Imaging : Sensing, Reconstruction, and Target Detection. IEEE Signal Process. Mag. 31(1): 116-126 (2014) - [j15]Peng Guan, Maxim Raginsky, Rebecca M. Willett
:
Online Markov Decision Processes With Kullback-Leibler Control Cost. IEEE Trans. Autom. Control. 59(6): 1423-1438 (2014) - [c50]Peng Guan, Maxim Raginsky, Rebecca Willett
:
From minimax value to low-regret algorithms for online Markov decision processes. ACC 2014: 471-476 - [c49]Albert K. Oh, Zachary T. Harmany, Rebecca M. Willett
:
To e or not to e in poisson image reconstruction. ICIP 2014: 2829-2833 - [i16]Peng Guan, Maxim Raginsky, Rebecca Willett:
Online Markov decision processes with Kullback-Leibler control cost. CoRR abs/1401.3198 (2014) - [i15]Eric C. Hall, Rebecca M. Willett:
Tracking Dynamic Point Processes on Networks. CoRR abs/1409.0031 (2014) - 2013
- [j14]Yao Xie
, Jiaji Huang, Rebecca Willett
:
Change-Point Detection for High-Dimensional Time Series With Missing Data. IEEE J. Sel. Top. Signal Process. 7(1): 12-27 (2013) - [j13]