Berkeley




Contact Information

Phone:  +1 510 643 9352 
Fax:    +1 510 643 7846

Office: EECS Department
        273 Cory Hall 
        Berkeley, CA 94720

Email:  x@y  with
        x = alyson   
        y=eecs DOT berkeley DOT edu

Alyson K. Fletcher

Allie
Allie
Lola



  • Publications

  • Awards

  • Teaching Experience

  • Full CV



    • I am a postdoctoral fellow with Professor Martin Vetterli in the Wireless Foundations Research Center at the Department of Electrical Engineering and Computer Science of the University of California, Berkeley. I received my M.S. and Ph.D. in EE from the University of California at Berkeley with Professor Kannan Ramchandran in the BASiCS research group. I received my M.A. in Mathematics from the University of California at Berkeley.

    My most recent research is in sparse approximation and its connections to compression and communication. More generally, I am interested in statistical signal processing, nonlinear inverse problems, high-dimensional data, machine learning, wavelet-based image processing, LMI optimization methods, and estimation of Markov dynamical systems. I am concerned with both theoretical foundations and algorithms in these areas, and I employ a range of analytic tools from information theory, control systems and optimization. My work has applications in estimation algorithms , audio and image processing, and wireless communications.

    My research has been supported by a National Science Foundation Graduate Fellowship, the Henry Luce Foundation, Soroptimist International, and Sigma Xi.


    Wifo EECS Department Math Department Wireless Foundations BASiCS UC Berkeley

    Publications

    Theses:

    Doctoral Dissertation : Electrical Engineering, University of California, Berkeley, January 2006.
    A Jump Linear Framework for Estimation and Robust Communication with Markovian Source and Channel Dynamics,
    Committee: Kannan Ramchandran, Venkat Anantharam, Alexandre J. Chorin

    Master's Thesis: Mathematics, University of California, Berkeley, May 2005.
    Estimation via Sparse Approximation: Error Bounds and Random Frame Analysis,
    Committee: F. Alberto Grünbaum, David J. Aldous, Bin Yu

    Master's Thesis : Electrical Engineering, University of California, Berkeley, May 2002.
    Denoising via Recursive Wavelet Thresholding,
    Committee: Kannan Ramchandran, Laurent El Ghaoui


    Journal:

    A. K. Fletcher, S. Rangan, and V. K. Goyal, Necessary and Sufficient Conditions on Sparsity Pattern Recovery, IEEE Trans. Information Theory, revised January 2009; submitted and available on arXiv, April 2008. Revised Version Jan2009

    A. K. Fletcher, S. Rangan and V. K. Goyal, On-Off Random Access Channels: A Compressed Sensing Framework submitted to IEEE Trans. Information Theory and arXived.

    V. K. Goyal, A. K. Fletcher, and S. Rangan, Distributed Coding of Sparse Signals , chapter in Distributed Source Coding: Theory, Algorithms, and Applications, P. L. Dragotti and M. Gastpar eds., Academic Press, 2009.

    V. K. Goyal, A. K. Fletcher, and S. Rangan, Compressive Sampling and Lossy Compression , IEEE Signal Processing Magazine, vol.25, no.2, pp.48--56, March 2008

    A. K. Fletcher, S. Rangan, V. K. Goyal, and K. Ramchandran, Robust Predictive Quantization: Analysis and Design via Convex Optimization , IEEE J. Selected Topics in Signal Processing, vol.1, no.4, pp.618--632, December 2007

    A. K. Fletcher, S. Rangan, V. K. Goyal, and K. Ramchandran, Denoising by Sparse Approximation: Error Bounds Based on Rate--Distortion Theory , EURASIP J. Applied Signal Processing, Special Issue on Frames and Overcomplete Representations, vol. 2006, March 2006

    *A. K. Fletcher and K. Ramchandran On Multiple-Observation Denoising with Threshold Operators, in preparation for IEEE Trans. Image Processing,

    *A. K. Fletcher, S. Rangan and V. K. Goyal, Estimation and Approximation of Signals using Random Subspaces, in preparation for IEEE Trans. Information Theory

    *A. K. Fletcher, S. Rangan, and V. K. Goyal, On the Rate-Distortion Performance of Compressed Sensing, in preparation for IEEE Trans. Signal Processing.


    Conference and symposium papers :

    A. K. Fletcher, S. Rangan, and V. K. Goyal, Random Access Channels: A Compressed Sensing Framework' Wavelets XIII, SPIE Optics \& Photonics 2009. (invited)

    *A. K. Fletcher, S. Rangan and V. K. Goyal, A Sparsity Detection Framework for On Off Random Access Channels submitted to IEEE Int. Symp. Information Theory 2009.

    A. K. Fletcher, S. Rangan, and V. K. Goyal, Resolution Limits of Sparse Coding in High Dimensions, Proc. Neural Information Processing Systems Conf. 2008 (Vancouver, Canada, December 8-11). [* Acceptance rate of 24% *]

    A. K. Fletcher, S. Rangan, and V. K. Goyal, On Subspace Structure in Source and Channel Coding, Proc. IEEE Int. Symp. Information Theory 2008 (Toronto, Canada, July 6-11), pp. 1982-1986.

    A. K. Fletcher, S. Rangan, and V. K. Goyal, Rate-Distortion Bounds for Sparse Approximation, Proc. IEEE Workshop on Statistical Signal Processing 2007 (Madison, WI, August 26-29), pp. 254-258.

    A. K. Fletcher, S. Rangan, and V. K. Goyal, On the Rate-Distortion Performance of Compressed, Sensing, Proc. IEEE Int. Conf. Acoustics, Speech, & Signal Processing 2007 (Honolulu, HI, April 15-20), vol. III, pp. 885-888.

    A. K. Fletcher, S. Rangan, V. K. Goyal, and K. Ramchandran, Causal and Strictly Causal Estimation for Jump Linear Systems: An LMI Analysis, Proc. Conf. Information Sciences & Systems 2006 (Princeton, NJ, March 22-24), pp. 1302-1307.

    A. K. Fletcher, S. Rangan, V. K. Goyal, and K. Ramchandran, Analysis of Denoising by Sparse Approximation with Random Frame Asymptotics, Proc. IEEE Int. Symp. on Information Theory 2005 (Adelaide, September 4-9), pp. 1706-1710.

    A. K. Fletcher, S. Rangan, and V. K. Goyal, Sparse Approximation, Denoising, and Large Random Frames, Proc. Wavelets XI, part of SPIE Optics & Photonics 2005 (San Diego, CA, July 31-August 4), vol. 5914, pp. 172-181.

    A. K. Fletcher, S. Rangan, V. K. Goyal, and K. Ramchandran Optimized Filtering and Reconstruction in Predictive Quantization with Losses, Proc. IEEE Int. Conf. Image Processing 2004 (Singapore, October 24-27), vol. 5, pp. 3245-3248.

    A. K. Fletcher, S. Rangan, V. K. Goyal, and K. Ramchandran, Robust Predictive Quantization: A New Design and Optimization Methodology, Proc. IEEE Int. Symp. Information Theory 2004 (Chicago, IL, June 27-July 2), p. 427.

    A. K. Fletcher, S. Rangan, and V. K. Goyal, Estimation from Lossy Sensor Data: Jump Linear Modeling and LMI Analysis, Proc. ACM/IEEE International Conference on Information Processing in Sen sor Networks 2004 (Berkeley, CA, April 26-27), pp. 251-258.

    A. K. Fletcher, V. K. Goyal, and K. Ramchandran, On Multivariate Estimation by Thresholding, Proc. IEEE Int. Conf. Image Processing 2003 (Barcelona, Spain, September 14-17), vol. 1, pp. 61-64.

    A. K. Fletcher and K. Ramchandran, Estimation Error Bounds for Denoising by Sparse Approximation, Proc. IEEE Int. Conf. Image Processing 2003 (Barcelona, Spain, September 14-17), vol. 1, pp. 113-116.

    A. K. Fletcher, V. K. Goyal, and K. Ramchandran, Iterative Projective Wavelet Methods for Denoising, Proc. Wavelets X: Applications in Signal & Image Processing, part of SPIE Int. Symp. on Optical Science & Technology 2003 (San Diego, CA, August 3-8), vol. 5207, pp. 9-15.

    A. K. Fletcher and K. Ramchandran, Estimation Error Bounds for Frame Denoising, Proc. Wavelets X: Applications in Signal & Image Processing, part of SPIE Int. Symp. on Optical Science & Technology 2003 (San Diego, CA, August 3-8), vol. 5207, pp. 40-46.

    A. K. Fletcher, K. Ramchandran, and V. K. Goyal, Wavelet Denoising by Recursive Cycle Spinning, Proc. IEEE Int. Conf. Image Processing 2002 (Rochester, NY, September 22-25), vol. 2, pp. 873-876.


    Invited Presentations & Workshops

    DIMACS/DyDAn Working Group & Workshop on Streaming, Coding, and Compressive Sensing: Unifying Theory and Common Applications to Sparse Signal Data Analysis and Processing, March 25--27, 2009.
    Invited workshop speaker & invitation--only working group participant.

    Random Access Channels and Sparsity Detection University of California at San Diego Information Theory and Applications Workshop, February 8-13, 2009.

    Frames for the Finite World: Sampling, coding, and quantization, American Institute for Mathematics, Workshop, Fall 2008.

    Banff International Research Station Workshop on Mentoring for Engineering Academia II, July 22-27, 2007 (invited participant), Banff, Alberta, Canada.

    Compressed Sensing as a Source Coding Technique' 2007 von Neumann Symposium on Sparse Representation and High-Dimensional Geometry, July 8–12, 2007, Snowbird, UT.

    On Encoding with a Codebook of Subspaces,” University of California at San Diego Information Theory and Applications Workshop, January 29, 2007.

    Rate-Distortion Performance of Sparse-Signal Coding with Random Measurements, SIAM Conference on Imaging Science, May 15, 2006, Minneapolis, MN.

    University of California at San Diego Workshop on Information Theory and Its Applications, February 6–10, 2006 (invited participant).

    Estimation and Robust Communication of Signals with Markovian Losses,” ´Ecole Polytechnique F´ed´erale de Lausanne, Computer and Communication Sciences Department, July 14, 2005, Lausanne, Switzerland.

    “Estimation with Markovian Dynamics and Sparseness,” University of California, Berkeley, Networking/Communication/DSP Seminar, April 20, 2005, Berkeley, CA.

    UCLA Institute for Pure and Applied Mathematics (IPAM) Program on Multiscale Geometry and Analysis in High Dimensions, Fall 2004.

    PAESMEM/Stanford School of Engineering Workshop on Mentoring in Engineering, June 21–22, 2004.

    “Sparseness from Redundancy: Denoising Methods and Bounds,” University of Cambridge, Department of Engineering, Signal Processing Seminar, October 2, 2003, Cambridge, England.

    “Wavelet Denoising by Recursive Cycle Spinning,” DIMACS Workshop on Source Coding and Harmonic Analysis, May 9, 2002, New Brunswick, NJ.