Stephen Becker

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 63

Top Topics

Convex Optimization

Top Venues

IEEE Signal Process. Mag.

J. Optim. Theory Appl.

Publications

Nuojin Cheng, Osman Asif Malik, Yiming Xu, Stephen Becker, Alireza Doostan, Akil Narayan
Subsampling of Parametric Models with Bifidelity Boosting. SIAM/ASA J. Uncertain. Quantification 12 (2) (2024)
Nuojin Cheng, Stephen Becker
Variational Entropy Search for Adjusting Expected Improvement. CoRR (2024)
Jacob Spainhour, Korben Smart, Stephen Becker, Nick Bottenus
Optimization of Array Encoding for Ultrasound Imaging. CoRR (2024)
Kevin Doherty, Cooper Simpson, Stephen Becker, Alireza Doostan
QuadConv: Quadrature-based convolutions with applications to non-uniform PDE data compression. J. Comput. Phys. 498 (2024)
Angran Li, Stephen Becker, Alireza Doostan
Online randomized interpolative decomposition with a posteriori error estimator for temporal PDE data reduction. CoRR (2024)
Riccardo Balin, Filippo Simini, Cooper Simpson, Andrew Shao, Alessandro Rigazzi, Matthew Ellis, Stephen Becker, Alireza Doostan, John A. Evans, Kenneth E. Jansen
In Situ Framework for Coupling Simulation and Machine Learning with Application to CFD. CoRR (2023)
Nuojin Cheng, Osman Asif Malik, Stephen Becker, Alireza Doostan
Bi-fidelity Variational Auto-encoder for Uncertainty Quantification. CoRR (2023)
Mitchell Krock, William Kleiber, Dorit Hammerling, Stephen Becker
Modeling Massive Highly Multivariate Nonstationary Spatial Data with the Basis Graphical Lasso. J. Comput. Graph. Stat. 32 (4) (2023)
Osman Asif Malik, Yiming Xu, Nuojin Cheng, Stephen Becker, Alireza Doostan, Akil Narayan
Fast Algorithms for Monotone Lower Subsets of Kronecker Least Squares Problems. CoRR (2022)
Kevin Doherty, Cooper Simpson, Stephen Becker, Alireza Doostan
QCNN: Quadrature Convolutional Neural Network with Application to Unstructured Data Compression. CoRR (2022)
Nuojin Cheng, Osman Asif Malik, Yiming Xu, Stephen Becker, Alireza Doostan, Akil Narayan
Quadrature Sampling of Parametric Models with Bi-fidelity Boosting. CoRR (2022)
Farhad Pourkamali-Anaraki, Mohammad Amin Hariri-Ardebili, Stephen Becker, Maziar Raissi
Call for Special Issue Papers: Big Scientific Data and Machine Learning in Science and Engineering: Deadline for Manuscript Submission: February 1, 2022. Big Data 9 (5) (2021)
Richard J. Clancy, Stephen Becker
Approximate maximum likelihood estimators for linear regression with design matrix uncertainty. CoRR (2021)
David Kozak, Stephen Becker, Alireza Doostan, Luis Tenorio
A stochastic subspace approach to gradient-free optimization in high dimensions. Comput. Optim. Appl. 79 (2) (2021)
Osman Asif Malik, Stephen Becker
A Sampling-Based Method for Tensor Ring Decomposition. ICML (2021)
Farhad Pourkamali-Anaraki, Mohammad Amin Hariri-Ardebili, Stephen Becker, Maziar Raissi
Call for Special Issue Papers: Big Scientific Data and Machine Learning in Science and Engineering: Deadline for Manuscript Submission: February 1, 2022. Big Data 9 (4) (2021)
Zhishen Huang, Stephen Becker
Stochastic Gradient Langevin Dynamics with Variance Reduction. IJCNN (2021)
Farhad Pourkamali-Anaraki, Mohammad Amin Hariri-Ardebili, Stephen Becker, Maziar Raissi
Call for Special Issue Papers: Big Scientific Data and Machine Learning in Science and Engineering: Deadline for Manuscript Submission: February 1, 2022. Big Data 9 (6) (2021)
Mitchell Krock, William Kleiber, Dorit Hammerling, Stephen Becker
Modeling massive multivariate spatial data with the basis graphical lasso. CoRR (2021)
Zhishen Huang, Stephen Becker
Spectral estimation from simulations via sketching. J. Comput. Phys. 447 (2021)
Mitchell Krock, William Kleiber, Stephen Becker
Nonstationary Modeling With Sparsity for Spatial Data via the Basis Graphical Lasso. J. Comput. Graph. Stat. 30 (2) (2021)
Osman Asif Malik, Venkatalakshmi Vyjayanthi Narumanchi, Stephen Becker, Todd W. Murray
Superresolution Photoacoustic Tomography Using Random Speckle Illumination and Second Order Moments. WASPAA (2021)
Zhishen Huang, Stephen Becker
Stochastic Gradient Langevin Dynamics with Variance Reduction. CoRR (2021)
Liam Madden, Stephen Becker, Emiliano Dall'Anese
Bounds for the Tracking Error of First-Order Online Optimization Methods. J. Optim. Theory Appl. 189 (2) (2021)
Osman Asif Malik, Stephen Becker
Randomization of approximate bilinear computation for matrix multiplication. Int. J. Comput. Math. Comput. Syst. Theory 6 (1) (2021)
Osman Asif Malik, Stephen Becker
Fast randomized matrix and tensor interpolative decomposition using CountSketch. Adv. Comput. Math. 46 (6) (2020)
Emiliano Dall'Anese, Andrea Simonetto, Stephen Becker, Liam Madden
Optimization and Learning With Information Streams: Time-varying algorithms and applications. IEEE Signal Process. Mag. 37 (3) (2020)
Osman Asif Malik, Stephen Becker
A Sampling Based Method for Tensor Ring Decomposition. CoRR (2020)
Will Shand, Stephen Becker
Locality-sensitive hashing in function spaces. CoRR (2020)
Richard Clancy, Stephen Becker
Robust Least Squares for Quantized Data. CoRR (2020)
Farhad Pourkamali-Anaraki, James Folberth, Stephen Becker
Efficient Solvers for Sparse Subspace Clustering. Signal Process. 172 (2020)
James Folberth, Stephen Becker
Safe Feature Elimination for Non-negativity Constrained Convex Optimization. J. Optim. Theory Appl. 184 (3) (2020)
Lucas Laird, Richard C. Tillquist, Stephen Becker, Manuel E. Lladser
Resolvability of Hamming Graphs. SIAM J. Discret. Math. 34 (4) (2020)
Shuang Li, Stephen Becker, Michael B. Wakin
Nuclear Norm Based Spectrum Estimation for Molecular Dynamic Simulations. ACSSC (2020)
Zhishen Huang, Stephen Becker
Spectral estimation from simulations via sketching. CoRR (2020)
Stephen Becker, Richard Clancy
Robust least squares for quantized data matrices. Signal Process. 176 (2020)
Zhishen Huang, Stephen Becker
Perturbed Proximal Descent to Escape Saddle Points for Non-convex and Non-smooth Objective Functions. CoRR (2019)
Stephen Becker, Jalal Fadili, Peter Ochs
On Quasi-Newton Forward-Backward Splitting: Proximal Calculus and Convergence. SIAM J. Optim. 29 (4) (2019)
Osman Asif Malik, Stephen Becker
Fast Randomized Matrix and Tensor Interpolative Decomposition Using CountSketch. CoRR (2019)
Eric Kightley, Stephen Becker
One-Pass Sparsified Gaussian Mixtures. IEEE BigData (2019)
Zhishen Huang, Stephen Becker
Perturbed Proximal Descent to Escape Saddle Points for Non-convex and Non-smooth Objective Functions. INNSBDDL (2019)
James Folberth, Stephen Becker
Safe Feature Elimination for Non-Negativity Constrained Convex Optimization. CoRR (2019)
Eric Kightley, Stephen Becker
One-Pass Sparsified Gaussian Mixtures. CoRR (2019)
Farhad Pourkamali-Anaraki, Stephen Becker
Improved fixed-rank Nyström approximation via QR decomposition: Practical and theoretical aspects. Neurocomputing 363 (2019)
Derek Driggs, Stephen Becker, Aleksandr Y. Aravkin
Adapting Regularized Low-Rank Models for Parallel Architectures. SIAM J. Sci. Comput. 41 (1) (2019)
Emiliano Dall'Anese, Andrea Simonetto, Stephen Becker, Liam Madden
Optimization and Learning with Information Streams: Time-varying Algorithms and Applications. CoRR (2019)
Lucas Laird, Richard C. Tillquist, Stephen Becker, Manuel E. Lladser
Resolvability of Hamming Graphs. CoRR (2019)
Richard Border, Stephen Becker
Stochastic Lanczos estimation of genomic variance components for linear mixed-effects models. BMC Bioinform. 20 (1) (2019)
Liam Madden, Stephen Becker, Emiliano Dall'Anese
Online Sparse Subspace Clustering. DSW (2019)
Jessica A. Gronski, Mohamed Amin Ben Sassi, Stephen Becker, Sriram Sankaranarayanan
Template polyhedra and bilinear optimization. Formal Methods Syst. Des. 54 (1) (2019)
Osman Asif Malik, Stephen Becker
Guarantees for the Kronecker Fast Johnson-Lindenstrauss Transform Using a Coherence and Sampling Argument. CoRR (2019)
Osman Asif Malik, Stephen Becker
Randomization of Approximate Bilinear Computation for Matrix Multiplication. CoRR (2019)
Farhad Pourkamali-Anaraki, Stephen Becker, Michael B. Wakin
Randomized Clustered Nystrom for Large-Scale Kernel Machines. AAAI (2018)
Farhad Pourkamali-Anaraki, Stephen Becker
Efficient Solvers for Sparse Subspace Clustering. CoRR (2018)
Osman Asif Malik, Stephen Becker
Low-Rank Tucker Decomposition of Large Tensors Using TensorSketch. NeurIPS (2018)
Farhad Pourkamali-Anaraki, Stephen Becker
Improved Fixed-Rank Nyström Approximation via QR Decomposition: Practical and Theoretical Aspects. CoRR (2017)
Farhad Pourkamali-Anaraki, Stephen Becker
Preconditioned Data Sparsification for Big Data With Applications to PCA and K-Means. IEEE Trans. Inf. Theory 63 (5) (2017)
Stephen Becker, Ban Kawas, Marek Petrik
Robust Partially-Compressed Least-Squares. AAAI (2017)
James Folberth, Stephen Becker
Efficient Adjoint Computation for Wavelet and Convolution Operators [Lecture Notes]. IEEE Signal Process. Mag. 33 (6) (2016)
Farhad Pourkamali-Anaraki, Stephen Becker
A randomized approach to efficient kernel clustering. GlobalSIP (2016)
Aleksandr Y. Aravkin, Stephen Becker
Dual Smoothing and Level Set Techniques for Variational Matrix Decomposition. CoRR (2016)
Rafael M. Frongillo, Ian A. Kash, Stephen Becker
Open Problem: Property Elicitation and Elicitation Complexity. COLT (2016)
Farhad Pourkamali-Anaraki, Stephen Becker
Randomized Clustered Nystrom for Large-Scale Kernel Machines. CoRR (2016)
John J. Bruer, Joel A. Tropp, Volkan Cevher, Stephen Becker
Designing Statistical Estimators That Balance Sample Size, Risk, and Computational Cost. IEEE J. Sel. Top. Signal Process. 9 (4) (2015)
Farhad Pourkamali-Anaraki, Stephen Becker, Shannon M. Hughes
Efficient Dictionary Learning via Very Sparse Random Projections. CoRR (2015)
Farhad Pourkamali-Anaraki, Stephen Becker
Preconditioned Data Sparsification for Big Data with Applications to PCA and K-means. CoRR (2015)
Stephen Becker, Ban Kawas, Marek Petrik, Karthikeyan Natesan Ramamurthy
Robust Partially-Compressed Least-Squares. CoRR (2015)
Aleksandr Y. Aravkin, Stephen Becker, Volkan Cevher, Peder A. Olsen
A variational approach to stable principal component pursuit. UAI (2014)
John J. Bruer, Joel A. Tropp, Volkan Cevher, Stephen Becker
Time-Data Tradeoffs by Aggressive Smoothing. NIPS (2014)
Volkan Cevher, Stephen Becker, Mark Schmidt
Convex Optimization for Big Data: Scalable, randomized, and parallel algorithms for big data analytics. IEEE Signal Process. Mag. 31 (5) (2014)
Volkan Cevher, Stephen Becker, Mark Schmidt
Convex Optimization for Big Data. CoRR (2014)
Christos Tzagkarakis, Stephen Becker, Athanasios Mouchtaris
Joint low-rank representation and matrix completion under a singular value thresholding framework. EUSIPCO (2014)
Cho-Jui Hsieh, Inderjit S. Dhillon, Pradeep Ravikumar, Stephen Becker, Peder A. Olsen
QUIC & DIRTY: A Quadratic Approximation Approach for Dirty Statistical Models. NIPS (2014)
Bubacarr Bah, Stephen Becker, Volkan Cevher, Baran Gozcu
Metric learning with rank and sparsity constraints. ICASSP (2014)
Emmanuel J. Candès, Stephen Becker
Compressive sensing: Principles and hardware implementations. ESSCIRC (2013)
Stephen Becker, Volkan Cevher, Anastasios Kyrillidis
Randomized Low-Memory Singular Value Projection CoRR (2013)
Anastasios Kyrillidis, Stephen Becker, Volkan Cevher, Christoph Koch
Sparse simplex projections for portfolio optimization. GlobalSIP (2013)
Anastasios Kyrillidis, Stephen Becker, Volkan Cevher, Christoph Koch
Sparse projections onto the simplex. ICML (2) (2013)
Michael B. Wakin, Stephen Becker, Eric B. Nakamura, Michael C. Grant, Emilio A. Sovero, Daniel Ching, Juhwan Yoo, Justin K. Romberg, Azita Emami-Neyestanak, Emmanuel J. Candès
A Nonuniform Sampler for Wideband Spectrally-Sparse Environments. IEEE J. Emerg. Sel. Topics Circuits Syst. 2 (3) (2012)
Juhwan Yoo, Christopher K. Turnes, Eric B. Nakamura, Chi K. Le, Stephen Becker, Emilio A. Sovero, Michael B. Wakin, Michael C. Grant, Justin K. Romberg, Azita Emami-Neyestanak, Emmanuel J. Candès
A Compressed Sensing Parameter Extraction Platform for Radar Pulse Signal Acquisition. IEEE J. Emerg. Sel. Topics Circuits Syst. 2 (3) (2012)
Juhwan Yoo, Stephen Becker, Manuel Monge, Matthew Loh, Emmanuel J. Candès, Azita Emami-Neyestanak
Design and implementation of a fully integrated compressed-sensing signal acquisition system. ICASSP (2012)
Stephen Becker, Mohamed-Jalal Fadili
A quasi-Newton proximal splitting method. NIPS (2012)
Anastasios Kyrillidis, Stephen Becker, Volkan Cevher
Sparse projections onto the simplex CoRR (2012)
Stephen Becker, Jérôme Bobin, Emmanuel J. Candès
NESTA: A Fast and Accurate First-Order Method for Sparse Recovery. SIAM J. Imaging Sci. 4 (1) (2011)
Stephen Becker, Emmanuel J. Candès, Michael C. Grant
Templates for convex cone problems with applications to sparse signal recovery. Math. Program. Comput. 3 (3) (2011)