Deanna Needell
#48,859
Most Influential Person Now
American mathematician
Deanna Needell's AcademicInfluence.com Rankings
Deanna Needellmathematics Degrees
Mathematics
#3165
World Rank
#4731
Historical Rank
Applied Mathematics
#322
World Rank
#349
Historical Rank
Measure Theory
#2039
World Rank
#2472
Historical Rank
Download Badge
Mathematics
Why Is Deanna Needell Influential?
(Suggest an Edit or Addition)According to Wikipedia, Deanna Needell is an American applied mathematician at the University of California, Los Angeles. She authors The Needell in the Haystack, a column published in the Girls' Angle Bulletin. Education Deanna Needell received her PhD in mathematics from the University of California, Davis in 2009. Her dissertation title was Topics in Compressed Sensing.
Deanna Needell's Published Works
Number of citations in a given year to any of this author's works
Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author
Published Works
- CoSaMP: Iterative signal recovery from incomplete and inaccurate samples (2008) (4576)
- Uniform Uncertainty Principle and Signal Recovery via Regularized Orthogonal Matching Pursuit (2007) (996)
- Compressed Sensing with Coherent and Redundant Dictionaries (2010) (906)
- Signal Recovery From Incomplete and Inaccurate Measurements Via Regularized Orthogonal Matching Pursuit (2007) (875)
- Stochastic gradient descent, weighted sampling, and the randomized Kaczmarz algorithm (2013) (478)
- Stable Image Reconstruction Using Total Variation Minimization (2012) (235)
- Randomized Kaczmarz solver for noisy linear systems (2009) (228)
- Paved with Good Intentions: Analysis of a Randomized Block Kaczmarz Method (2012) (220)
- Convergence Properties of the Randomized Extended Gauss-Seidel and Kaczmarz Methods (2015) (145)
- Signal Space CoSaMP for Sparse Recovery With Redundant Dictionaries (2012) (130)
- Acceleration of randomized Kaczmarz method via the Johnson–Lindenstrauss Lemma (2010) (123)
- Exponential Decay of Reconstruction Error From Binary Measurements of Sparse Signals (2014) (109)
- Greedy signal recovery review (2008) (101)
- Randomized block Kaczmarz method with projection for solving least squares (2014) (99)
- Noisy signal recovery via iterative reweighted L1-minimization (2009) (96)
- Linear Convergence of Stochastic Iterative Greedy Algorithms With Sparse Constraints (2014) (87)
- Near-Optimal Compressed Sensing Guarantees for Total Variation Minimization (2012) (86)
- Signal Recovery from Inaccurate and Incomplete Measurements via Regularized Orthogonal Matching Pursuit (2010) (78)
- Topics in Compressed Sensing (2009) (72)
- A Sampling Kaczmarz-Motzkin Algorithm for Linear Feasibility (2016) (65)
- Two-Subspace Projection Method for Coherent Overdetermined Systems (2012) (56)
- Uniqueness conditions for low-rank matrix recovery (2011) (46)
- Compressive sensing with redundant dictionaries and structured measurements (2015) (46)
- Weighted ℓ1-Minimization for Sparse Recovery under Arbitrary Prior Information (2016) (41)
- Rows versus Columns: Randomized Kaczmarz or Gauss-Seidel for Ridge Regression (2015) (40)
- Greedy signal recovery and uncertainty principles (2008) (36)
- Stochastic gradient descent and the randomized Kaczmarz algorithm (2013) (36)
- Batched Stochastic Gradient Descent with Weighted Sampling (2016) (32)
- Greedy Signal Space Methods for incoherence and beyond (2013) (32)
- Randomized Kaczmarz with averaging (2020) (32)
- Super-resolution via superset selection and pruning (2013) (32)
- One-Bit Compressive Sensing of Dictionary-Sparse Signals (2016) (30)
- On Motzkin’s method for inconsistent linear systems (2018) (29)
- Methods for quantized compressed sensing (2015) (29)
- Mixed operators in compressed sensing (2010) (29)
- CoSaMP (2010) (29)
- Constrained Adaptive Sensing (2015) (28)
- Block Kaczmarz Method with Inequalities (2014) (26)
- On block Gaussian sketching for the Kaczmarz method (2019) (24)
- Compressed Sensing and Dictionary Learning (2014) (23)
- On Adaptive Sketch-and-Project for Solving Linear Systems (2021) (22)
- Online matrix factorization for Markovian data and applications to Network Dictionary Learning (2019) (20)
- Stochastic Gradient Descent for Linear Systems with Missing Data (2017) (18)
- Biquasiles and dual graph diagrams (2016) (17)
- An algebraic perspective on integer sparse recovery (2018) (17)
- Robust CUR Decomposition: Theory and Imaging Applications (2021) (17)
- Random Vector Functional Link Networks for Function Approximation on Manifolds (2020) (16)
- Adaptive Sketch-and-Project Methods for Solving Linear Systems (2019) (16)
- Quantile-based Iterative Methods for Corrupted Systems of Linear Equations (2020) (14)
- An Approximate Message Passing Framework for Side Information (2018) (14)
- Signal recovery from incomplete and inaccurate measurements via ROMP (2007) (14)
- An Introduction to Fourier Analysis with Applications to Music (2014) (14)
- One-bit Compressive Sensing with partial support (2015) (13)
- Lower Memory Oblivious (Tensor) Subspace Embeddings with Fewer Random Bits: Modewise Methods for Least Squares (2019) (13)
- Non-Asymptotic Theory of Random Matrices (2006) (12)
- De-biasing low-rank projection for matrix completion (2017) (12)
- Simple Classification using Binary Data (2017) (12)
- Weighted Matrix Completion From Non-Random, Non-Uniform Sampling Patterns (2019) (11)
- Mode-wise Tensor Decompositions: Multi-dimensional Generalizations of CUR Decompositions (2021) (11)
- Randomized Projection Methods for Linear Systems with Arbitrarily Large Sparse Corruptions (2018) (11)
- Iterative Methods for Solving Factorized Linear Systems (2017) (10)
- Fast Robust Tensor Principal Component Analysis via Fiber CUR Decomposition * (2021) (10)
- IRG2016: RBF-based regional geoid model of Iran (2018) (10)
- Near oracle performance and block analysis of signal space greedy methods (2014) (9)
- Two-Part Reconstruction With Noisy-Sudocodes (2014) (9)
- Two-part reconstruction in compressed sensing (2013) (9)
- COVID-19 Time-series Prediction by Joint Dictionary Learning and Online NMF (2020) (9)
- Kaczmarz Algorithm with Soft Constraints for User Interface Layout (2013) (9)
- On a Guided Nonnegative Matrix Factorization (2020) (8)
- On Nonnegative Matrix and Tensor Decompositions for COVID-19 Twitter Dynamics (2020) (8)
- Matrix Completion for Structured Observations (2018) (8)
- Analysis of Fast Structured Dictionary Learning (2018) (7)
- Sketching for Motzkin’s Iterative Method for Linear Systems (2019) (7)
- Boltzmann enhancements of biquasile counting invariants (2017) (7)
- Iterative hard thresholding for low CP-rank tensor models (2019) (7)
- Stochastic Greedy Algorithms For Multiple Measurement Vectors (2017) (7)
- Neural Nonnegative Matrix Factorization for Hierarchical Multilayer Topic Modeling (2019) (6)
- Total variation minimization for stable multidimensional signal recovery (2012) (6)
- Semi-supervised NMF Models for Topic Modeling in Learning Tasks (2020) (6)
- Sparse Randomized Kaczmarz for Support Recovery of Jointly Sparse Corrupted Multiple Measurement Vectors (2017) (6)
- Improving image clustering using sparse text and the wisdom of the crowds (2014) (6)
- On Large-Scale Dynamic Topic Modeling with Nonnegative CP Tensor Decomposition (2020) (5)
- Practical approximate projection schemes in greedy signal space methods (2014) (5)
- Online nonnegative tensor factorization and CP-dictionary learning for Markovian data (2020) (5)
- A Gradient Descent Approach for Incomplete Linear Systems (2018) (5)
- COVID-19 Literature Topic-Based Search via Hierarchical NMF (2020) (5)
- Tribracket Modules (2018) (5)
- Antibiotic Treatment Response in Chronic Lyme Disease: Why Do Some Patients Improve While Others Do Not? (2020) (5)
- A Bayesian Approach for Asynchronous Parallel Sparse Recovery (2018) (5)
- A Practical Study of Longitudinal Reference Based Compressed Sensing for MRI (2016) (5)
- Modified fuzzy clustering with segregated cluster centroids (2019) (5)
- Lattices from tight equiangular frames (2016) (5)
- Near-optimal compressed sensing guarantees for anisotropic and isotropic total variation minimization (2013) (5)
- Optimizing Quantization for Lasso Recovery (2016) (5)
- Learning to Predict Human Stress Level with Incomplete Sensor Data from Wearable Devices (2019) (5)
- An asynchronous parallel approach to sparse recovery (2017) (4)
- Sparse Reconstruction of Regional Gravity Signal Based on Stabilized Orthogonal Matching Pursuit (SOMP) (2016) (4)
- Applications of Online Nonnegative Matrix Factorization to Image and Time-Series Data (2020) (4)
- Conditional approximate message passing with side information (2017) (4)
- Spectral Clustering: An empirical study of Approximation Algorithms and its Application to the Attrition Problem (2012) (4)
- An Adaptation for Iterative Structured Matrix Completion (2020) (3)
- On block Gaussian sketching for iterative projections (2019) (3)
- Fast Hyperspectral Diffuse Optical Imaging Method with Joint Sparsity (2019) (3)
- Lattices From Tight Frames and Vertex Transitive Graphs (2019) (3)
- Testing Positive Semidefiniteness Using Linear Measurements (2022) (3)
- Lattices from equiangular tight frames (2016) (3)
- A note on practical approximate projection schemes in signal space methods (2015) (3)
- Analysis of Spatial and Spatiotemporal Anomalies Using Persistent Homology: Case Studies with COVID-19 Data (2021) (3)
- Bias of Homotopic Gradient Descent for the Hinge Loss (2019) (3)
- Using Correlated Subset Structure for Compressive Sensing Recovery (2013) (3)
- Robust recovery of bandlimited graph signals via randomized dynamical sampling (2021) (3)
- Guaranteed sparse signal recovery with highly coherent sensing matrices (2013) (2)
- Greedy algorithms in super-resolution (2014) (2)
- Selectable Set Randomized Kaczmarz (2021) (2)
- Compressed Anomaly Detection with Multiple Mixed Observations (2018) (2)
- Semi-supervised Nonnegative Matrix Factorization for Document Classification (2021) (2)
- Matrix Completion with Cross-Concentrated Sampling: Bridging Uniform Sampling and CUR Sampling (2022) (2)
- CoSaMP with redundant dictionaries (2012) (2)
- Randomized Projection Methods for Corrupted Linear Systems (2018) (2)
- The Manifold Scattering Transform for High-Dimensional Point Cloud Data (2022) (2)
- Near Oracle Performance of Signal Space Greedy Methods (2014) (2)
- Analysis of Spatiotemporal Anomalies Using Persistent Homology: Case Studies with COVID-19 Data (2021) (2)
- Tensor Completion through Total Variation with Initialization from Weighted HOSVD (2020) (2)
- D ec 2 01 6 Weighted l 1-Minimization for Sparse Recovery under Arbitrary Prior Information (2016) (2)
- Analysis of Legal Documents via Non-negative Matrix Factorization Methods (2021) (2)
- Stochastic Iterative Hard Thresholding for Low-Tucker-Rank Tensor Recovery (2019) (2)
- Online nonnegative CP-dictionary learning for Markovian data (2020) (2)
- Classification Scheme for Binary Data with Extensions (2019) (1)
- Hierarchical Classification using Binary Data (2018) (1)
- Inference of Media Bias and Content Quality Using Natural-Language Processing (2022) (1)
- Simple Object Classification Using Binary Data (2017) (1)
- Automatic Infectious Disease Classification Analysis with Concept Discovery (2022) (1)
- Detecting Short-lasting Topics Using Nonnegative Tensor Decomposition (preprint) (2020) (1)
- Two-Subspace Projection Method for Coherent Overdetermined Systems (2012) (1)
- Topic-aware chatbot using Recurrent Neural Networks and Nonnegative Matrix Factorization (2019) (1)
- Neural Nonnegative CP Decomposition for Hierarchical Tensor Analysis (2021) (1)
- Stochastic Gradient Descent Variants for Corrupted Systems of Linear Equations (2020) (1)
- Feature Selection from Lyme Disease Patient Survey Using Machine Learning (2020) (1)
- Geometric Scattering on Measure Spaces (2022) (1)
- Online Signal Recovery via Heavy Ball Kaczmarz (2022) (1)
- Feature Selection on Lyme Disease Patient Survey Data (2020) (1)
- Signal Recovery with Regularized OMP (2009) (1)
- On the Mathematics of Music: From Chords to Fourier Analysis (2013) (1)
- Tolerant compressed sensing with partially coherent sensing matrices (2016) (1)
- An iterative method for classification of binary data (2018) (1)
- Large Data Analysis and Lyme Disease (2019) (1)
- Sketched Gaussian Model Linear Discriminant Analysis via the Randomized Kaczmarz Method (2022) (1)
- HOSVD-Based Algorithm for Weighted Tensor Completion (2020) (1)
- J ul 2 00 7 Algorithm : Regularized Orthogonal Matching Pursuit ( ROMP ) (2008) (1)
- QuantileRK: Solving Large-Scale Linear Systems with Corrupted, Noisy Data (2021) (1)
- SP2: A Second Order Stochastic Polyak Method (2022) (1)
- Guided Semi-Supervised Non-negative Matrix Factorization on Legal Documents (2022) (1)
- Guided Semi-Supervised Non-Negative Matrix Factorization (2022) (1)
- Multi-Randomized Kaczmarz for Latent Class Regression (2022) (0)
- Reconstructing Piezoelectric Responses over a Lattice: Adaptive Sampling of Low Dimensional Time Series Representations Based on Relative Isolation and Gradient Size (2021) (0)
- Stochastic gradient descent, weighted sampling, and the randomized Kaczmarz algorithm (2015) (0)
- Less is More: Robust image recovery via total variation minimization (2012) (0)
- Population-Based Hierarchical Non-Negative Matrix Factorization for Survey Data (2022) (0)
- On block Gaussian sketching for the Kaczmarz method (2020) (0)
- On Audio Enhancement via Online Non-Negative Matrix Factorization (2021) (0)
- ALGORITHMS ON APACHE SPARK SUBMITTED TO PROFESSOR (0)
- Bias of Homotopic Gradient Descent for the Hinge Loss (2020) (0)
- Linear Convergence of Reshuffling Kaczmarz Methods With Sparse Constraints (2023) (0)
- Algorithm: Regularized Orthogonal Matching Pursuit (ROMP) (2007) (0)
- Randomized Kaczmarz with averaging (2020) (0)
- On Nonnegative CP Tensor Decomposition Robustness to Noise (2020) (0)
- Continuous Semi-Supervised Nonnegative Matrix Factorization (2022) (0)
- On Motzkin’s method for inconsistent linear systems (2018) (0)
- Stochastic Greedy Methods with Sparse Constraints (2015) (0)
- Data-driven Algorithm Selection and Parameter Tuning: Two Case studies in Optimization and Signal Processing (2019) (0)
- An Untrained One-layer Convolutional Network-based Method for Line Spectral Estimation (2021) (0)
- Federated Gradient Matching Pursuit (2023) (0)
- A Convergence Rate for Manifold Neural Networks (2022) (0)
- Analysis of Fast Alternating Minimization for Structured Dictionary Learning (2018) (0)
- Modewise Operators, the Tensor Restricted Isometry Property, and Low-Rank Tensor Recovery (2021) (0)
- On block accelerations of quantile randomized Kaczmarz for corrupted systems of linear equations (2022) (0)
- Convergence of Iterative Hard Thresholding Variants with Application to Asynchronous Parallel Methods for Sparse Recovery (2019) (0)
- Data-driven algorithm selection and tuning in optimization and signal processing (2020) (0)
- Block Kaczmarz Method with Inequalities (2014) (0)
- A comparison of clustering and missing data methods for health sciences (2014) (0)
- Multi-scale Hybridized Topic Modeling: A Pipeline for Analyzing Unstructured Text Datasets via Topic Modeling (2022) (0)
- Clustering of Nonnegative Data and an Application to Matrix Completion (2020) (0)
- A Generalized Hierarchical Nonnegative Tensor Decomposition (2021) (0)
- Matrix Completion with Selective Sampling (2019) (0)
- 6-6-2014 Two-Part Reconstruction with Noisy-Sudocodes (2014) (0)
- Distributed randomized Kaczmarz for the adversarial workers (2022) (0)
- One-Bit Quadratic Compressed Sensing: From Sample Abundance to Linear Feasibility (2023) (0)
- N A ] 1 1 D ec 2 00 8 GREEDY SIGNAL RECOVERY REVIEW (2018) (0)
- Data-driven algorithm selection and tuning in optimization and signal processing (2020) (0)
- Statistical Learning for Best Practices in Tattoo Removal (2021) (0)
- Jointly Sparse Signal Recovery with Prior Info (2019) (0)
- On Inferences from Completed Data (2019) (0)
- An Iterative Method for Structured Matrix Completion (2020) (0)
- Iterative Singular Tube Hard Thresholding Algorithms for Tensor Completion (2023) (0)
- White Paper: “Computational Microscopy” (IPAM Long Program, Fall 2022) (0)
- A Challenge for the Millennium: the Million Dollar Problems in Mathematics (2013) (0)
This paper list is powered by the following services:
Other Resources About Deanna Needell
What Schools Are Affiliated With Deanna Needell?
Deanna Needell is affiliated with the following schools:
