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- Mark A. Iwen
- Foundations of Computational Mathematics
- 2010
We study the problem of estimating the best k term Fourier representation for a given frequency-sparse signal (i.e., vector) A of length N k. More explicitly, we investigate how to deterministically… (More)
- Mark A. Iwen
- 2009 Conference Record of the Forty-Third…
- 2009
We consider the recovery of sparse signals, f ∈ ℝ<sup>N</sup>, containing at most k ≪ N nonzero entries using linear measurements contaminated with i.i.d. Gaussian background… (More)
- Mark A. Iwen
- SODA
- 2008
We study the problem of estimating the best <i>B</i> term Fourier representation for a given frequency-sparse signal (i.e., vector) <b>A</b> of length <i>N</i> ≫ <i>B.</i> More precisely, we… (More)
- Mark A. Iwen, Mauro Maggioni
- ArXiv
- 2012
This paper considers the approximate reconstruction of points, ~x ∈ RD, which are close to a given compact d-dimensional submanifold, M, of RD using a small number of linear measurements of ~x. In… (More)
- Mark A. Iwen, Craig V. Spencer
- 2008 42nd Annual Conference on Information…
- 2008
This paper improves on the best-known runtime and measurement bounds for a recently proposed Deterministic sublinear-time Sparse Fourier Transform algorithm (hereafter called DSFT). In (Iwen, 2008 ),… (More)
- Mark A. Iwen, Craig V. Spencer
- Inf. Process. Lett.
- 2009
We consider the conjectured O(N2+ ) time complexity of multiplying any two N × N matrices A and B. Our main result is a deterministic Compressed Sensing (CS) algorithm that both rapidly and… (More)
- J. Bailey, Mark A. Iwen, Craig V. Spencer
- SIAM J. Matrix Analysis Applications
- 2012
We present a general class of compressed sensing matrices which are then demonstrated to have associated sublinear-time sparse approximation algorithms. We then develop methods for constructing… (More)
- Mark A. Iwen, Ahmed H. Tewfik
- IEEE Transactions on Signal Processing
- 2012
This paper studies the problem of recovering a signal with a sparse representation in a given orthonormal basis using as few noisy observations as possible. Herein, observations are subject to the… (More)
- Mark A. Iwen, Willis Lang, Jignesh M. Patel
- 2008 IEEE 24th International Conference on Data…
- 2008
Current state-of-the-art association rule-based classifiers for gene expression data operate in two phases: (i) Association rule mining from training data followed by (ii) Classification of query… (More)
- Guangliang Chen, Mark A. Iwen, Sang Chin, Mauro Maggioni
- 2012 Visual Communications and Image Processing
- 2012
Data sets are often modeled as samples from some probability distribution lying in a very high dimensional space. In practice, they tend to exhibit low intrinsic dimensionality, which enables both… (More)