# overview
I have research interests in compressive sensing; Approximation Theory (especially Spline Functions and Minimal Projections);

computational mathematics; bioinformatics; and data science.

# keywords[]
4603 Computer Vision And Multimedia Computation

# keywords[]
4603 Computer Vision And Multimedia Computation

# keywords[]
Real Mutually Unbiased Equiangular Tight Frames

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Restricted Isometry Property Adapted To A Dictionary

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30 Agricultural, Veterinary And Food Sciences

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4603 Computer Vision And Multimedia Computation

# keywords[]
4603 Computer Vision And Multimedia Computation

# educationAndTraining[].organization.label
Ecole Centrale de Lyon - (Écully, Rhone-Alpes, France)

# educationAndTraining[].organization.label
University of Cambridge - (Cambridge, United Kingdom)

# publications[].label
Stability and Robustness of Weak Orthogonal Matching Pursuits

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Learning from Non-Random Data in Hilbert Spaces: An Optimal Recovery  Perspective

# publications[].label
De-biasing low-rank projection for matrix completion

# publications[].publisher
SPIE, the international society for optics and photonics

# publications[].label
On maximal relative projection constants

# publications[].label
Instances of Computational Optimal Recovery: Dealing with Observation  Errors

# publications[].label
On the sparsity of LASSO minimizers in sparse data recovery

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Sparse recovery from saturated measurements (R)

# publications[].label
HARD THRESHOLDING PURSUIT: AN ALGORITHM FOR COMPRESSIVE SENSING

# publications[].publisher
Society for Industrial & Applied Mathematics (SIAM)

# publications[].label
Iterative Hard Thresholding for Low-Rank Recovery from Rank-One  Projections

# publications[].label
On the exact constant in Jackson-Stechkin inequality for the uniform  metric

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One-Bit Sensing of Low-Rank and Bisparse Matrices

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On the value of the fifth maximal projection constant

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Exponential decay of reconstruction error from binary measurements of  sparse signals

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A Mathematical Introduction to Compressive Sensing

# publications[].label
Sparse Recovery Algorithms: Sufficient Conditions in Terms of Restricted Isometry Constants

# publications[].label
Learning from non-random data in Hilbert spaces: an optimal recovery perspective

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Determining projection constants of univariate polynomial spaces

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A note on guaranteed sparse recovery via l(1)-minimization

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Quikr: a method for rapid reconstruction of bacterial communities via compressive sensing.

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Sparsest solutions of underdetermined linear systems via l(q)-minimization for 0 < q <= 1

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Weighted matrix completion from non-random, non-uniform sampling  patterns

# publications[].label
Full Recovery from Point Values: an Optimal Algorithm for Chebyshev  Approximability Prior

# publications[].label
Complexity of multivariate problems based on binary information

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
The Gelfand widths of l(p)-balls for 0 < p <= 1

# publications[].label
On the value of the fifth maximal projection constant

# publications[].label
Approximability Models and Optimal System Identification

# publications[].label
Instances of Computational Optimal Recovery: Dealing with Observation   Errors

# publications[].label
Sparse Recovery from Inaccurate Saturated Measurements

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The Gelfand widths of $ell_p$-balls for $0<pleq 1$

# publications[].label
Sparse disjointed recovery from noninflating measurements

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On the norms and minimal properties of de la Vallee Poussin's type operators

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On the value of the max-norm of the orthogonal projector onto splines with multiple knots

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Sparse recovery with pre-Gaussian random matrices

# publications[].publisher
Institute of Mathematics, Polish Academy of Sciences

# publications[].label
On the Sparsity of LASSO Minimizers in Sparse Data Recovery

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Allometry constants of finite-dimensional spaces: theory and computations

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Computation of Minimal Projections and Extensions

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On the best conditioned bases of quadratic polynomials

# publications[].label
Jointly Low-Rank and Bisparse Recovery: Questions and Partial Answers

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Instances of computational optimal recovery: Refined approximability models

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One-Bit Compressive Sensing of Dictionary-Sparse Signals

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On the Exact Constant in the Jackson-Stechkin Inequality for the Uniform Metric

# publications[].label
Mathematical Pictures at a Data Science Exhibition

# publications[].label
Sparse Recovery by Means of Nonnegative Least Squares

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Instances of Computational Optimal Recovery: Refined Approximability  Models

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GENERATING DIMENSION FORMULAS FOR MULTIVARIATE SPLINES.

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Basc: constrained approximation by semidefinite programming

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Stability and robustness of l(1)-minimizations with Weibull matrices and redundant dictionaries

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Optimal Recovery from Inaccurate Data in Hilbert Spaces: Regularize, But What of the Parameter?

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Real versus complex null space properties for sparse vector recovery

# publications[].label
Instances of Computational Optimal Recovery: Dealing with Observation Errors*

# publications[].publisher
Society for Industrial & Applied Mathematics (SIAM)

# publications[].label
An IHT Algorithm for Sparse Recovery From Subexponential Measurements

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Optimal Recovery from Inaccurate Data in Hilbert Spaces: Regularize, but  what of the Parameter?

# publications[].label
Determining Projection Constants of Univariate Polynomial Spaces

# publications[].label
Nonlinear Approximation and (Deep) ReLU Networks

# publications[].label
Computation of Chebyshev Polynomials for Union of Intervals

# publications[].label
Exponential Decay of Reconstruction Error From Binary Measurements of Sparse Signals

# publications[].publisher
Institute of Electrical and Electronics Engineers (IEEE)

# publications[].label
Hard thresholding pursuit algorithms: Number of iterations

# publications[].label
Open questions around the spline orthoprojector

# researcherOn[].label
CDS&E-MSS: Recovery of High-Dimensional Structured Functions

# researcherOn[].awardedBy.label
National Science Foundation - (Arlington, Virginia, United States)

# streetAddress
Texas A&M University; Mathematics; 3368 TAMU