Andrew Thompson's homepage
Departmental Lecturer in Computational Mathematics, University of Oxford
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Publications
  • The Cascading Haar Wavelet algorithm for computing the Walsh-Hadamard Transform; IEEE Signal Processing Letters 24(7) p1020-1023 (2017).
  • Dual-wavelength pump-probe microscopy analysis of melanin composition; Scientific Reports 6 (2016) (with F. Robles, J. Wilson, S. Deb, R. Calderbank and W. Warren).
  • Quantitative recovery conditions for tree-based compressed sensing; IEEE Transactions on Information Theory 63(3) p1-17 (2016) (with C. Cartis); extended technical report.
  • Data Representation using the Weyl Transform; IEEE Transactions on Signal Processing 64(7) p1844-1853 (2016) (with Q. Qiu, R. Calderbank and G. Sapiro).
  • Modified DCTNet for audio signals classification; The Journal of the Acoustical Society of America 140(4) (2016) (with Y. Xian, Y. Pu, Z. Gan and L. Liang).
  • On block coherence of frames; Applied and Computational Harmonic Analysis 38(1) p50-71 (2015) (with R. Calderbank and Y. Xie).
  • A new and improved quantitative recovery analysis for iterative hard thresholding algorithms in compressed sensing; IEEE Transactions on Information Theory 61(4) p1-24 (2015) (with C. Cartis).
  • An exact tree projection algorithm for wavelets; IEEE Signal Processing Letters 20(11) p1028-1031 (2013) (with C. Cartis). Matlab code for the algorithm is here.
  • Phase Transitions for Greedy Sparse Approximation Algorithms; Applied and Computational Harmonic Analysis 30(2) p188-203 (2011) (with J. Blanchard, C. Cartis and J. Tanner).
  • On Support Sizes of Restricted Isometry Constants; Applied and Computational Harmonic Analysis 29(3) p382-390 (2010) (with J. Blanchard).
  • Conference proceedings and preprints
  • CHIRRUP: a practical algorithm for unsourced multiple access; preprint (2018) (with R. Calderbank).
  • Non-negative super-resolution is stable; accepted, IEEE Data Science Workshop (2018) (with A. Eftekhari, J. Tanner, B. Toader and H. Tyagi).
  • A Bridge Between Past and Present: Exchange and Conditional Gradient Methods are Equivalent; preprint (2018) (with A. Eftekhari).
  • Sparse non-negative super-resolution — simplified and stabilised; preprint (2018) (with A. Eftekhari, J. Tanner, B. Toader and H. Tyagi).
  • Compressed Neighbour Discovery using Sparse Kerdock Matrices; accepted, International Symposium on Information Theory (2018) (with R. Calderbank).
  • Sparse near-equiangular tight frames with applications in full duplex wireless communication; Global Conference on Signal and Information Processing, Montreal, Canada (2017) (with R. Calderbank).
  • Compressive imaging using fast transform coding; Proceedings of the SPIE 9992, Emerging Imaging and Sensing Technologies (2016) (with R. Calderbank).
  • Sketching for Sequential Change-Point Detection; Global Conference on Signal and Information Processing, Orlando, USA (2015) (with Y. Xie and M. Wang).
  • Representation using the Weyl Transform; International Conference on Learning Representations, San Diego, USA (2015) (with Q. Qiu, R. Calderbank and G. Sapiro).
  • Classification of whale vocalizations using the Weyl Transform; International Conference on Acoustics, Speech and Signal Processing, Brisbane, Australia (2015) (with Y. Xian, Q. Qiu, L. Nolte, J. Lu, R. Calderbank and D. Nowacek).
  • Compressive Single-Pixel Imaging; IMA Conference on Mathematics in Defence, Defence Academy, Shrivenham, UK (2011).
  • Compressive Single-Pixel Imaging; Technical Report ERGO 11-006 (2011). This report relates to an internship carried out at SELEX Galileo Ltd, Edinburgh.
  • Pushing the RIP Phase Transition in Compressed Sensing; European Signal Processing Conference, Aalborg, Denmark (2010) (with J. Blanchard).
  • PhD thesis
  • Quantitative analysis of algorithms for compressed signal recovery; School of Mathematics, University of Edinburgh; supervisor: Coralia Cartis (2012).
  • Slides
  • The Cascading Haar Wavelet algorithm for computing the Walsh-Hadamard Transform (Global Conference on Signal and Information Processing; Nov 2017).
  • Sparse near-equiangular tight frames with applications in full duplex wireless communication (Global Conference on Signal and Information Processing; Nov 2017).
  • Patch Weyl Transform convolutional filters for learning image texture features (IMA Conference on the Mathematical Challenges of Big Data; Dec 2016).
  • Compressive imaging using fast transform coding (SPIE Security+Defence: Emerging Imaging and Sensing Technologies; Sep 2016).
  • Constructing matrices with optimal block coherence (SIAM Annual Meeting, Chicago, USA; Jul 2014).
  • A tree projection algorithm for wavelet-based sparse approximation (Biennial Conference on Numerical Analysis and Optimization, Strathclyde, UK; Jun 2013).
  • Compressive single-pixel imaging (IMA conference on Mathematics in Defence, Defence Academy, UK; Oct 2011).
  • A new recovery analysis of Iterative Hard Thresholding for compressed sensing (Signal Processing with Adaptive Sparse Structured Representations, Edinburgh, UK; Jun 2011).
  • On support sizes of restricted isometry constants (British Applied Mathematics Colloquium, Edinburgh, UK; Apr 2010).
  • Phase transitions for greedy sparse approximation algorithms (Curves and Surfaces, Avignon, France; Jun 2010).
  • Contact
    Mathematical Institute
    University of Oxford
    Andrew Wiles Building
    Woodstock Road
    Oxford
    OX2 6GG.
    phone: 01865 273579
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