Clayton Webster

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All published works

Action	Title	Year	Authors
+ PDF Chat	Anisotropic Gaussian Smoothing for Gradient-based Optimization	2024	Andrew Starnes Guannan Zhang Viktor Reshniak Clayton Webster
+ PDF Chat	Mamba for Scalable and Efficient Personalized Recommendations	2024	Andrew Starnes Clayton Webster
+ PDF Chat	Increasing Entropy to Boost Policy Gradient Performance on Personalization Tasks	2023	Andrew Starnes Anton Dereventsov Clayton Webster
+	Increasing Entropy to Boost Policy Gradient Performance on Personalization Tasks	2023	Andrew Starnes Anton Dereventsov Clayton Webster
+	Gaussian smoothing stochastic gradient descent (GSmoothSGD)	2023	Andrew Starnes Clayton Webster
+	Gaussian smoothing gradient descent for minimizing high-dimensional non-convex functions	2023	Andrew Starnes Anton Dereventsov Clayton Webster
+	Special issue dedicated to Professor Max Gunzburger on the occasion of his 75th birthday	2022	Pavel Bochev Marta D’Elia Qiang Du Steve Hou Clayton Webster Guannan Zhang
+ PDF Chat	An asymptotically compatible probabilistic collocation method for randomly heterogeneous nonlocal problems	2022	Yiming Fan Xiaochuan Tian Xiu Yang Xingjie Li Clayton Webster Yue Yu
+ PDF Chat	Analysis of sparse recovery for Legendre expansions using envelope bound	2022	Hoang Tran Clayton Webster
+ PDF Chat	Issue Information	2022	Clayton Webster George F. Pinder J. R. Whiteman Ismael Herrera Marta D’Elia Lili Ju Guannan Zhang Muhammad Hamid Muhammad Usman Wei Wang
+	Sparse Polynomial Approximation of High-Dimensional Functions	2022	Ben Adcock Simone Brugiapaglia Clayton Webster
+	Examining Policy Entropy of Reinforcement Learning Agents for Personalization Tasks	2022	Anton Dereventsov Andrew Starnes Clayton Webster
+ PDF Chat	On the Unreasonable Efficiency of State Space Clustering in Personalization Tasks	2021	Anton Dereventsov Ranga Raju Vatsavai Clayton Webster
+ PDF Chat	An Adaptive Stochastic Gradient-Free Approach for High-Dimensional Blackbox Optimization	2021	Anton Dereventsov Clayton Webster Joseph Daws
+ PDF Chat	On the Strong Convergence of Forward-Backward Splitting in Reconstructing Jointly Sparse Signals	2021	Nick Dexter Hoang Tran Clayton Webster
+	On the Unreasonable Efficiency of State Space Clustering in Personalization Tasks	2021	Anton Dereventsov Ranga Raju Vatsavai Clayton Webster
+	Offline Policy Comparison under Limited Historical Agent-Environment Interactions	2021	Anton Dereventsov Joseph Daws Clayton Webster
+ PDF Chat	Robust Learning with Implicit Residual Networks	2020	Viktor Reshniak Clayton Webster
+	Robust Learning with Implicit Residual Networks	2020	Viktor Reshniak Clayton Webster
+ PDF Chat	Closure Learning for Nonlinear Model Reduction Using Deep Residual Neural Network	2020	Xuping Xie Clayton Webster Traian Iliescu
+ PDF Chat	A Nonlocal Feature-Driven Exemplar-Based Approach for Image Inpainting	2020	Viktor Reshniak Jeremy Trageser Clayton Webster
+	Analysis of The Ratio of $\ell_1$ and $\ell_2$ Norms in Compressed Sensing	2020	Yiming Xu Akil Narayan Hoang Tran Clayton Webster
+	An adaptive stochastic gradient-free approach for high-dimensional blackbox optimization	2020	Anton Dereventsov Clayton Webster Joseph Daws
+	A class of null space conditions for sparse recovery via nonconvex, non-separable minimizations	2019	Hoang Tran Clayton Webster
+	A Weighted 𝓁 1 -Minimization Approach For Wavelet Reconstruction of Signals and Images.	2019	Joseph Daws Armenak Petrosyan Hoang Tran Clayton Webster
+	A mixed <i>ℓ</i><sub>1</sub> regularization approach for sparse simultaneous approximation of parameterized PDEs	2019	Nick Dexter Hoang Tran Clayton Webster
+	Reconstructing high-dimensional Hilbert-valued functions via compressed sensing	2019	Nick Dexter Hoang Tran Clayton Webster
+ PDF Chat	Reconstruction of jointly sparse vectors via manifold optimization	2019	Armenak Petrosyan Hoang Tran Clayton Webster
+	A Polynomial-Based Approach for Architectural Design and Learning with Deep Neural Networks.	2019	Joseph Daws Clayton Webster
+	Greedy Shallow Networks: A New Approach for Constructing and Training Neural Networks	2019	Anton Dereventsov Armenak Petrosyan Clayton Webster
+	The Natural Greedy Algorithm for reduced bases in Banach spaces	2019	Anton Dereventsov Clayton Webster
+	Reconstructing high-dimensional Hilbert-valued functions via compressed sensing	2019	Nick Dexter Hoang Tran Clayton Webster
+	Analytic Continuation of Noisy Data Using Adams Bashforth ResNet	2019	Xuping Xie Feng Bao Thomas Maier Clayton Webster
+	Neural network integral representations with the ReLU activation function	2019	Armenak Petrosyan Anton Dereventsov Clayton Webster
+	Closure Learning for Nonlinear Model Reduction Using Deep Residual Neural Network	2019	Xuping Xie Clayton Webster Traian Iliescu
+	Analysis of Deep Neural Networks with Quasi-optimal polynomial approximation rates	2019	Joseph Daws Clayton Webster
+	A Weighted $\ell_1$-Minimization Approach For Wavelet Reconstruction of Signals and Images	2019	Joseph Daws Armenak Petrosyan Hoang Tran Clayton Webster
+	Reconstructing high-dimensional Hilbert-valued functions via compressed sensing	2019	Nick Dexter Hoang Tran Clayton Webster
+	The Natural Greedy Algorithm for reduced bases in Banach spaces	2019	Anton Dereventsov Clayton Webster
+	A Polynomial-Based Approach for Architectural Design and Learning with Deep Neural Networks	2019	Joseph Daws Clayton Webster
+	Greedy Shallow Networks: An Approach for Constructing and Training Neural Networks	2019	Anton Dereventsov Armenak Petrosyan Clayton Webster
+	Reconstruction of jointly sparse vectors via manifold optimization	2018	Armenak Petrosyan Hoang Tran Clayton Webster
+	Evolve Then Filter Regularization for Stochastic Reduced Order Modeling	2018	Xuping Xie Feng Bao Clayton Webster
+	An Improved Discrete Least-Squares/Reduced-Basis Method for Parameterized Elliptic PDEs	2018	Max Gunzburger Michael Schneier Clayton Webster Guannan Zhang
+ PDF Chat	On the Lebesgue constant of weighted Leja points for Lagrange interpolation on unbounded domains	2018	Peter Jantsch Clayton Webster Guannan Zhang
+	Non-intrusive inference reduced order model for fluids using linear multistep neural network	2018	Xuping Xie Guannan Zhang Clayton Webster
+	Analysis of sparse recovery for Legendre expansions using envelope bound	2018	Hoang Tran Clayton Webster
+	Reconstruction of jointly sparse vectors via manifold optimization	2018	Armenak Petrosyan Hoang Tran Clayton Webster
+	On the Strong Convergence of Forward-Backward Splitting in Reconstructing Jointly Sparse Signals	2017	Nick Dexter Hoang Tran Clayton Webster
+	Unified sufficient conditions for uniform recovery of sparse signals via nonconvex minimizations	2017	Hoang Tran Clayton Webster
+	A class of null space conditions for sparse recovery via nonconvex, non-separable minimizations	2017	Hoang Tran Clayton Webster
+	Polynomial approximation via compressed sensing of high-dimensional functions on lower sets	2017	Abdellah Chkifa Nick Dexter Hoang Tran Clayton Webster
+ PDF Chat	Analysis of quasi-optimal polynomial approximations for parameterized PDEs with deterministic and stochastic coefficients	2017	Hoang Tran Clayton Webster Guannan Zhang
+	Polynomial approximation of high-dimensional functions via compressed sensing	2017	Ben Adcock Simone Brugiapaglia Clayton Webster
+	An improved discrete least-squares/reduced-basis method for parameterized elliptic PDEs	2017	Max Gunzburger Michael Schneier Clayton Webster Guannan Zhang
+ PDF Chat	Compressed Sensing Approaches for Polynomial Approximation of High-Dimensional Functions	2017	Ben Adcock Simone Brugiapaglia Clayton Webster
+	A class of null space conditions for sparse recovery via nonconvex, non-separable minimizations	2017	Hoang Tran Clayton Webster
+	Compressed sensing approaches for polynomial approximation of high-dimensional functions	2017	Ben Adcock Simone Brugiapaglia Clayton Webster
+ PDF Chat	Fast and efficient stochastic optimization for analytic continuation	2016	Feng Bao Yanfei Tang Michael S. Summers Guannan Zhang Clayton Webster V. W. Scarola Thomas Maier
+	Explicit cost bounds of stochastic Galerkin approximations for parameterized PDEs with random coefficients	2016	Nick Dexter Clayton Webster Guannan Zhang
+ PDF Chat	A Sparse Grid Method for Bayesian Uncertainty Quantification with Application to Large Eddy Simulation Turbulence Models	2016	Hoang Tran Clayton Webster Guannan Zhang
+	On the Lebesgue Constant of Weighted Leja Points for Lagrange Interpolation on Unbounded Domains	2016	Peter Jantsch Clayton Webster Guannan Zhang
+	Hyperspherical Sparse Approximation Techniques for High-Dimensional Discontinuity Detection	2016	Guannan Zhang Clayton Webster Max Gunzburger John Burkardt
+ PDF Chat	Accelerating Stochastic Collocation Methods for Partial Differential Equations with Random Input Data	2016	D. Galindo Peter Jantsch Clayton Webster Guannan Zhang
+ PDF Chat	Numerical methods for a class of nonlocal diffusion problems with the use of backward SDEs	2015	Guannan Zhang Weidong Zhao Clayton Webster Max Gunzburger
+	Numerical solution of backward stochastic differential equations with jumps for a class of nonlocal diffusion problems	2015	Guannan Zhang Weidong Zhao Clayton Webster Max Gunzburger
+ PDF Chat	Numerical Analysis of Fixed Point Algorithms in the Presence of Hardware Faults	2015	Miroslav Stoyanov Clayton Webster
+ PDF Chat	A Multilevel Stochastic Collocation Method for Partial Differential Equations with Random Input Data	2015	Aretha L. Teckentrup Peter Jantsch Clayton Webster Max Gunzburger
+	An Efficient Meshfreee Implicit Filter for Nonlinear Filtering Problems	2015	Feng Bao Yanzhao Cao Clayton Webster Guannan Zhang
+	A Dynamically Adaptive Sparse Grid Method for Quasi-Optimal Interpolation of Multidimensional Analytic Functions	2015	Miroslav Stoyanov Clayton Webster
+	Analysis of quasi-optimal polynomial approximations for parameterized PDEs with deterministic and stochastic coefficients	2015	Hoang Tran Clayton Webster Guannan Zhang
+	Numerical Methods for a Class of Nonlocal Diffusion Problems with the Use of Backward SDEs	2015	Guannan Zhang Weidong Zhao Clayton Webster Max Gunzburger
+	Accelerating stochastic collocation methods for partial differential equations with random input data	2015	Diego Galindo Peter Jantsch Clayton Webster Guannan Zhang
+	A sparse grid method for Bayesian uncertainty quantification with application to large eddy simulation turbulence models	2015	Hoang Tran Clayton Webster Guannan Zhang
+ PDF Chat	A GRADIENT-BASED SAMPLING APPROACH FOR DIMENSION REDUCTION OF PARTIAL DIFFERENTIAL EQUATIONS WITH STOCHASTIC COEFFICIENTS	2014	Miroslav Stoyanov Clayton Webster
+ PDF Chat	A Sparse Grid Method for Bayesian Uncertainty Quantification with Application to Large Eddy Simulation Turbulence Models	2014	Hoang Tran Clayton Webster Guannan Zhang
+	A Multilevel Stochastic Collocation Method for Partial Differential Equations with Random Input Data	2014	Aretha L. Teckentrup Peter Jantsch Clayton Webster Max Gunzburger
+	Multilevel Acceleration of Stochastic Collocation Methods for PDEs with Random Input Data	2014	Max Gunzburger Peter Jantsch Aretha L. Teckentrup Clayton Webster
+	An Adaptive Wavelet Stochastic Collocation Method for Irregular Solutions of Partial Differential Equations with Random Input Data	2014	Max Gunzburger Clayton Webster Guannan Zhang
+	A Multilevel Stochastic Collocation Method for Partial Differential Equations with Random Input Data	2014	Aretha L. Teckentrup Peter Jantsch Clayton Webster Max Gunzburger
+	An adaptive wavelet stochastic collocation method for irregular solutions of stochastic partial differential equations	2012	Clayton Webster Guannan Zhang Max Gunzburger
+ PDF Chat	An adaptive sparse-grid high-order stochastic collocation method for Bayesian inference in groundwater reactive transport modeling	2012	Guannan Zhang Clayton Webster Max Gunzburger
+	A Sparse Grid Stochastic Collocation Method for Partial Differential Equations with Random Input Data	2008	Fabio Nobile Raúl Tempone Clayton Webster
+	The analysis of a sparse grid stochastic collocation method for partial differential equations with high-dimensional random input data.	2007	Clayton Webster Raúl Tempone Fabio Nobile

Common Coauthors

Coauthor	Papers Together
Guannan Zhang	25
Hoang Tran	24
Anton Dereventsov	14
Max Gunzburger	13
Peter Jantsch	8
Armenak Petrosyan	8
Joseph Daws	8
Nick Dexter	7
Andrew Starnes	7
Xuping Xie	5
Simone Brugiapaglia	4
Aretha L. Teckentrup	4
Ben Adcock	4
Viktor Reshniak	4
Miroslav Stoyanov	3
Feng Bao	3
Weidong Zhao	3
Traian Iliescu	2
Marta D’Elia	2
Raúl Tempone	2
Ranga Raju Vatsavai	2
Thomas Maier	2
Fabio Nobile	2
Michael Schneier	2
Farhad Fakhar‐Izadi	1
Soheil Salahshour	1
Imran Aziz	1
Xiu Yang	1
Rizwan Haq	1
Aylin Bayrak	1
Xingjie Li	1
Yiming Fan	1
Arezou Rezazadeh	1
Steve Hou	1
Abdellah Chkifa	1
D. Galindo	1
Muhammad Usman	1
Muhammad Hamid	1
Michael S. Summers	1
Wei Wang	1
Yiming Xu	1
Pavel Bochev	1
Nick Dexter	1
Feng Bao	1
John Burkardt	1
Ebru Ozbılge	1
Yue Yu	1
Ali Ahmadian	1
Yanzhao Cao	1
Jeremy Trageser	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	A Sparse Grid Stochastic Collocation Method for Partial Differential Equations with Random Input Data	2008	Fabio Nobile Raúl Tempone Clayton Webster	18
+ PDF Chat	ANALYTIC REGULARITY AND POLYNOMIAL APPROXIMATION OF PARAMETRIC AND STOCHASTIC ELLIPTIC PDE'S	2011	Albert Cohen Ronald DeVore Christoph Schwab	15
+ PDF Chat	Analysis of quasi-optimal polynomial approximations for parameterized PDEs with deterministic and stochastic coefficients	2017	Hoang Tran Clayton Webster Guannan Zhang	10
+ PDF Chat	Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information	2006	Emmanuel J. Candès Justin Romberg Terence Tao	10
+	Polynomial approximation via compressed sensing of high-dimensional functions on lower sets	2017	Abdellah Chkifa Nick Dexter Hoang Tran Clayton Webster	10
+	Dimension?Adaptive Tensor?Product Quadrature	2003	Thomas Gerstner Michael Griebel	9
+ PDF Chat	A non-adapted sparse approximation of PDEs with stochastic inputs	2011	Alireza Doostan Houman Owhadi	8
+ PDF Chat	Interpolation via weighted ℓ1 minimization	2015	Holger Rauhut Rachel Ward	8
+ PDF Chat	Compressive sensing Petrov-Galerkin approximation of high-dimensional parametric operator equations	2015	Holger Rauhut Christoph Schwab	8
+ PDF Chat	Infinite-Dimensional Compressed Sensing and Function Interpolation	2017	Ben Adcock	7
+	A method for numerical integration on an automatic computer	1960	C. W. Clenshaw A. R. Curtis	7
+ PDF Chat	On the Stability and Accuracy of Least Squares Approximations	2013	Albert Cohen Mark A. Davenport D. Leviatan	7
+	High-Order Collocation Methods for Differential Equations with Random Inputs	2005	Dongbin Xiu Jan S. Hesthaven	6
+	Adaptive sparse grid multilevel methods for elliptic PDEs based on finite differences	1998	Michael Griebel	6
+	Compressed sensing	2006	David L. Donoho	6
+	On asymptotics and estimates for the uniform norms of the Lagrange interpolation polynomials corresponding to the Chebyshev nodal points	1983	V K Dzjadyk В. В. Иванов	6
+ PDF Chat	Compressive sampling of polynomial chaos expansions: Convergence analysis and sampling strategies	2014	Jerrad Hampton Alireza Doostan	6
+ PDF Chat	Convergence rates for sparse chaos approximations of elliptic problems with stochastic coefficients	2006	Radu Alexandru Todor Christoph Schwab	6
+	Sparse Legendre expansions via <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si12.gif" display="inline" overflow="scroll"><mml:msub><mml:mrow><mml:mi>ℓ</mml:mi></mml:mrow><mml:mrow><mml:mn>1</mml:mn></mml:mrow></mml:msub></mml:math>-minimization	2012	Holger Rauhut Rachel Ward	6
+ PDF Chat	On polynomial chaos expansion via gradient-enhanced ℓ1-minimization	2016	Ji Peng Jerrad Hampton Alireza Doostan	5
+ PDF Chat	Ratio and difference of $l_1$ and $l_2$ norms and sparse representation with coherent dictionaries	2014	Penghang Yin Ernie Esser Jack Xin	5
+ PDF Chat	A Method for Finding Structured Sparse Solutions to Nonnegative Least Squares Problems with Applications	2013	Ernie Esser Yifei Lou Jack Xin	5
+ PDF Chat	Reduce and Boost: Recovering Arbitrary Sets of Jointly Sparse Vectors	2008	Moshe Mishali Yonina C. Eldar	5
+	Convex Analysis and Monotone Operator Theory in Hilbert Spaces	2017	Heinz H. Bauschke Patrick L. Combettes	5
+ PDF Chat	A weighted -minimization approach for sparse polynomial chaos expansions	2014	Ji Peng Jerrad Hampton Alireza Doostan	5
+	ON THE OPTIMAL POLYNOMIAL APPROXIMATION OF STOCHASTIC PDES BY GALERKIN AND COLLOCATION METHODS	2012	Joakim Beck Raúl Tempone Fabio Nobile Lorenzo Tamellini	5
+	Fixed-Point Continuation for $\ell_1$-Minimization: Methodology and Convergence	2008	Elaine Hale Wotao Yin Yin Zhang	5
+	Solving elliptic boundary value problems with uncertain coefficients by the finite element method: the stochastic formulation	2004	Ivo Babuška Raúl Tempone Georgios E. Zouraris	5
+	An Adaptive Wavelet Stochastic Collocation Method for Irregular Solutions of Partial Differential Equations with Random Input Data	2014	Max Gunzburger Clayton Webster Guannan Zhang	5
+	On Leja sequences: some results and applications	2003	Stefano De Marchı	5
+	Multilevel Monte Carlo methods and applications to elliptic PDEs with random coefficients	2011	K. A. Cliffe Michael B. Giles Robert Scheichl Aretha L. Teckentrup	4
+ PDF Chat	Subspace Methods for Joint Sparse Recovery	2012	Kiryung Lee Yoram Bresler Marius Junge	4
+ PDF Chat	Model-Based Compressive Sensing	2010	Richard G. Baraniuk Volkan Cevher Marco F. Duarte Chinmay Hegde	4
+ PDF Chat	Reversible Architectures for Arbitrarily Deep Residual Neural Networks	2018	Bo Chang Lili Meng Eldad Haber Lars Ruthotto David Begert Elliot Holtham	4
+ PDF Chat	Approximation of high-dimensional parametric PDEs	2015	Albert Cohen Ronald DeVore	4
+ PDF Chat	Rank Awareness in Joint Sparse Recovery	2012	Mike E. Davies Yonina C. Eldar	4
+	On sparse reconstruction from Fourier and Gaussian measurements	2007	Mark Rudelson Roman Vershynin	4
+ PDF Chat	Multi-level Monte Carlo Finite Element method for elliptic PDEs with stochastic coefficients	2011	Andrea Barth Christoph Schwab Nathaniel Zollinger	4
+ PDF Chat	Is Gauss Quadrature Better than Clenshaw–Curtis?	2008	Lloyd N. Trefethen	4
+	Sparse Approximate Solutions to Linear Systems	1995	B. K. Natarajan	3
+	The null space property for sparse recovery from multiple measurement vectors	2010	Ming‐Jun Lai Yang Liu	3
+	Compressed sensing and best 𝑘-term approximation	2008	Albert Cohen Wolfgang Dahmen Ronald DeVore	3
+ PDF Chat	Theoretical and Empirical Results for Recovery From Multiple Measurements	2010	E. van den Berg Michael P. Friedlander	3
+	Sparsest solutions of underdetermined linear systems via <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.gif" overflow="scroll"><mml:msub><mml:mi>ℓ</mml:mi><mml:mi>q</mml:mi></mml:msub></mml:math>-minimization for <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si2.gif" overflow="scroll"><mml:mn>0</mml:mn><mml:mo><</mml:mo><mml:mi>q</mml:mi><mml:mo>⩽</mml:mo><mml:mn>1</mml:mn></mml:math>	2008	Simon Foucart Ming‐Jun Lai	3
+	Explicit Cost Bounds of Algorithms for Multivariate Tensor Product Problems	1995	G.W. Wasilkowski H. Woźniakowski	3
+	Highly sparse representations from dictionaries are unique and independent of the sparseness measure	2006	Rémi Gribonval Morten Nielsen	3
+	Accelerating Markov Chain Monte Carlo Simulation by Differential Evolution with Self-Adaptive Randomized Subspace Sampling	2009	Jasper A. Vrugt Cajo J. F. ter Braak Cees Diks B.A. Robinson James M. Hyman David Higdon	3
+	None	2000	Volker Barthelmann Erich Novak Klaus Ritter	3
+	Finite Element Error Analysis of Elliptic PDEs with Random Coefficients and Its Application to Multilevel Monte Carlo Methods	2013	Julia Charrier Robert Scheichl Aretha L. Teckentrup	3
+	Characterization of discontinuities in high-dimensional stochastic problems on adaptive sparse grids	2011	John Jakeman Richard Archibald Dongbin Xiu	3