This section tends to lag in time! Please see CV for current list.
Theses
Highly-Selective Conferences
- A. K. Fletcher and S. Rangan,
Scalable Inference for Neuronal Connectivity from Calcium Imaging,
Proc. 28th Ann. Conf. Neural Information Processing Systems 2014.
[Acceptance rate: 25%, oral spotlight: top 4.9%]
- U. S. Kamilov, S. Rangan, A. K. Fletcher and M. Unser,
Approximate Message Passing with Consistent Parameter Estimation and Applications to Sparse Learning,
Proc. 26th Ann. Conf. Neural Information Processing Systems 2012.
[Acceptance rate: 25%.]
- A. K. Fletcher, S. Rangan, L. Varshney, A. Bhargava,
Neural Reconstruction with Approximate Message Passing (NeuRAMP),
Proc. 25th Ann. Conf. Neural Information Processing Systems 2011
(Granada, Spain, Dec. 13-15).
[Acceptance rate: 305/1400 = 22%.]
- A. K. Fletcher and S. Rangan,
Orthogonal Matching Pursuit from Noisy Random Measurements: A New Analysis,
Proc. 23rd Ann. Conf. Neural Information Processing Systems 2009
(Vancouver, Canada, Dec. 7-10).
[Acceptance rate: 24%. Spotlight paper, top 8%.]
- S. Rangan, A. K. Fletcher, and V. K. Goyal,
Asymptotic Analysis of MAP Estimation via the Replica Method and Compressed Sensing,
Proc. 23rd Ann. Conf. Neural Information Processing Systems 2009
(Vancouver, Canada, Dec. 7-10).
[Acceptance rate: 24%. Spotlight paper, top 8%.]
- A. K. Fletcher, S. Rangan, and V. K. Goyal,
Resolution Limits of Sparse Coding in High Dimensions,
Proc. 22nd Ann. Conf. Neural Information Processing Systems 2008.
[Acceptance rate: 250/1022 = 24%.]
- A. K. Fletcher, S. Rangan, and V. K. Goyal,
Estimation from Lossy Sensor Data: Jump Linear Modeling and LMI Analysis,
Proc. ACM/IEEE Int. Conf. Information Processing in Sensor Networks 2004
(Berkeley, CA, April 26-27), pp. 251-258.
[Acceptance rate oral presentation: 25/145=17%.]
Preprints
- A. K. Fletcher and S. Rangan,
Iterative Recontruction of Constrained Rank-One Matrices in Noise, arXiv:1202.2759, Dec. 2012.
Submitted to "Information and Inference, a Journal of the IMA", Sep. 2015.
- S. Rangan, P. Schniter, E. Riegler, A. K. Fletcher, V. Cevher,
Fixed Points of Generalized Approximate Message Passing with Arbitrary Matrices,
arXiv:1301.6295, Jan. 2013. Submitted to "IEEE Transactions on Information Theory", Aug. 2015.
- S. Rangan, A. K. Fletcher, P. Schniter, and U. Kamilov,
Inference for Generalized Linear Models via Alternating Directions and Bethe Free Energy Minimization,
submitted for publication, IEEE Trans. Information Theory, Oct. 2014.
- S. Rangan, A. K. Fletcher, V. K.Goyal and P. Schniter,
Hybrid Approximate Message Passing with Applications to Structured Sparsity,
arXiv:1111.2581, Nov. 2011.
- A. K. Fletcher, S. Rangan, and V. K. Goyal,
On-Off Random Access Channels: A Compressed Sensing Framework,
arXiv:0903.1022, March 2009.
Journal Papers
- U. S. Kamilov, S. Rangan, A. K. Fletcher and M. Unser,
Approximate Message Passing with Consistent Parameter Estimation and Applications to Sparse Learning",
IEEE Trans. Information Theory, 2014.
- A. K. Fletcher, V. K. Goyal and S. Rangan,
Ranked Sparse Signal Support Detection,
IEEE Trans. Signal Processing, 60(11):5919-5931, Nov. 2012.
- A. K. Fletcher and S. Rangan,
Orthogonal Matching Pursuit: A Brownian Motion Analysis,
IEEE Trans. Signal Processing, 60(3):1010-1021, March 2012.
- S. Rangan, A. K. Fletcher, and V. K. Goyal,
Asymptotic Analysis of MAP Estimation via the Replica Method and Applications to Compressed Sensing,
IEEE Trans. Information Theory, 58(3):1902-1923, March 2012.
- A. K. Fletcher, S. Rangan, and V. K. Goyal,
Necessary and Sufficient Conditions on Sparsity Recovery,
IEEE Trans. Information Theory, 55(12):5758-5772, Dec. 2009.
- V. K. Goyal, A. K. Fletcher, and S. Rangan,
Compressive Sampling and Lossy Compression,
IEEE Signal Processing Magazine, 25(2):48-56, March 2008.
- 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.
- 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, 1(4):618-632, Dec. 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.
Other Peer-Reviewed Conferences, Symposia, and Workshops
- A. K. Fletcher,. S. Rangan and J. Viventi,
Neural Mass Spatio-Temporal Modeling from High-Density
Electrode Array Recordings, Proc. IEEE Information Theory and Applications,
San Diego, CA, Feb. 2015
- P. Schniter, S. Rangan, and A. K. Fletcher, "Statistical Image Recovery: A Message-Passing Perspective,”
Int. Biomedical & Astronomical Signal Process. Frontiers Workshop (Villars sur-
Ollon, Switzerland, January 25–30, 2015.
- S. Rangan, A. K. Fletcher, P. Schniter,
On the Convergence of Approximate Message Passing for Arbitrary Matrices,
Proc. IEEE Int. Symp. Information Theory 2014 (Honolulu, HI, June 29-July 4).
- A. K. Fletcher,
Bayesian Inference of Neural Connectivity,
Proc. Comput. Syst. Neurosci. (Cosyne) 2014 (Snowbird, UT, Feb. 27-March 2).
- A. K. Fletcher, S. Rangan,
Hybrid Approximate Message Passing for Structured Group Sparsity,
Proc. Wavelets and Sparsity SPIE workshop, San Diego, Aug. 2013.
- S. Rangan, P. Schniter, E. Riegler, A. K. Fletcher, V. Cevher,
Fixed Points of Generalized Approximate Message Passing with Arbitrary Matrices,
Proc. IEEE Int. Symp. Information Theory (ISIT)
(Istanbul, Turkey), July 2013.
- A. K. Fletcher and S. Rangan,
Iterative Estimation of Constrained Rank-One Matrices in Noise,
Proc. IEEE Int. Symp. Information Theory (Cambridge, MA), July 2012.
- S. Rangan, A. K. Fletcher, V. K. Goyal, and P. Schniter,
Hybrid Generalized Approximate Message Passing with Applications to Structured Sparsity,
Proc. IEEE Int. Symp. Information Theory (Cambridge, MA), July 2012.
- S. Rangan, A. K. Fletcher, and V. K. Goyal,
Extensions of Replica Analysis to MAP Estimation with Applications to Compressed Sensing,
Proc. IEEE Int. Symp. Information Theory 2010 (Austin, TX, June 12-18),
pp. 1543-1547.
- A. K. Fletcher, S. Rangan, and V. K. Goyal,
Random Access Channels: A Compressed Sensing Framework
Proc. 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,
Proc. IEEE Int. Symp. Information Theory 2009
(Seoul, South Korea, June 28-July 3), pp. 169-173.
- 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, Aug. 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, Sept. 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-Aug. 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, Oct. 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, V. K. Goyal, and K. Ramchandran,
On Multivariate Estimation
by Thresholding,
Proc. IEEE Int. Conf. Image Processing 2003
(Barcelona, Spain, Sept. 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, Sept. 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, Aug. 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, Aug. 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, Sept. 22-25), vol. 2, pp. 873-876.
Selected Invited Talks and Workshops
- “Scalable Approaches to New Large-Scale Neuroscience,”
IEEE Signal Processing Society, Silicon Valley Chapter, November 5, 2015.
- “Scalable Inference of Neural Dynamical Systems,”
53rd Annual Allerton Conference on Communication, Control & Computing,
October 3, 2015.
- “Structured Estimation of Visual Receptive Fields,”
Bay Area Vision Research Day (BAVRD), September 18, 2015.
- “Inference for New Large-Scale Neuroscience,”
Mining and Modeling of Neuroscience Data, CRCNS/MSRI Summer School,
University of California, Berkeley, July 15, 2015.
- “Inferring Structure in Large Neural Systems,”
Mathematics & Statistics Department Seminar,
Boston University, March 19, 2015.
- “Inferring Structure in Large Neural Systems,”
Data Seminar: Departments of Mathematics, Electrical Engineering & Biomedical Engineering,
Duke University, March 13, 2015.
- “Inferring Structure in Large Neural Systems,”
Department of Statistics Seminar, University of California, Los Angeles,
March 10, 2015.
- “Inferring Structure in Large Neural Systems,”
Applied Mathematics & Statistics Department Seminar,
Johns Hopkins University, February 27, 2015.
- “Inferring Structure in Large Neural Systems,”
Applied Mathematics & Electrical Engineering Seminar,
Harvard University, February 25, 2015.
- “Inferring Structure in Large Neural Systems,”
Applied Mathematics Seminar, University of Washington, February 19, 2015.
- “Inferring Structure in Large Neural Systems,”
Department of Mathematics and Statistics Seminar,
University of San Francisco, February 10, 2015.
- “Uncovering Structure in Neural Systems,”
Information Theory and Applications Workshop,
February 6, 2015.
- Stanford Compression Forum, January 22, 2015.
- “Scalable Identification for Structured Nonlinear Neural Systems,”
Redwood Center for Theoretical Neuroscience Seminar, University of California, Berkeley, May 7, 2014.
- “Scalable Identification for Structured Nonlinear Neural Systems,”
ISL Big Data Seminar Series, Stanford University, April 10, 2014.
- “Bayesian Inference of Sparse Neural Dynamical Systems,”
Information Theory and Applications Workshop, University of California, San Diego, February 13, 2014.
- “Scalable Identification for Structured Nonlinear Neural Systems,”
University of California, Berkeley, Control Theory Seminar, February 3, 2014.
- “Scalable Identification for Structured Complex Nonlinear Systems,”
University of California, San Diego, ECE Seminar, January 30, 2014.
- Co-organizer, International Workshop on High-Dimensional Statistical Inference in the Brain,
Neural Information Process. Symp. (NIPS), 2013 (Lake Tahoe, NV, Dec 5-10).
- “Learning Sparse Priors in Approximate Message Passing,” Information Theory and Applications
Workshop, University of California, San Diego, February 13, 2013.
- “Neural Connectivity and Receptive Field Estimation via Hybrid Message Passing,” Information
Theory and Applications Workshop, University of California, San Diego, February 6, 2012.
- “Neural Connectivity and Receptive Field Estimation via Hybrid Message Passing,” Mathematical
EE Seminar, University of California, Santa Cruz. January 27, 2012.
- ”Sparsity: Algorithms and Applications in Neuroscience,” Applied Mathematics and Mathematical
Biology Seminar, Claremont Graduate University, January 25, 2012.
- “Exploiting Sparsity: Algorithms and Applications,” Electrical and Computer Engineering
Seminar, University of California, Davis, November 14, 2011.
- “Generalized Approximate Message Passing and Applications in Neural Receptive Field Estimation
and Connectomics,” Redwood Center for Theoretical Neuroscience, University of
California, Berkleley, June 8, 2011.
- “Algorithms for High-Dimensional Inference: Analysis and Applications,” University of California,
Davis Department of Electrical and Computer Engineering, May, 2011.
- “Algorithms for High-Dimensional Inference: Analysis and Applications,” University of Massachusetts
Department of Electrical and Computer Engineering, April 20, 2011.
- “Algorithms for High-Dimensional Inference: Analysis and Applications,” University of Florida
Department of Electrical and Computer Engineering, April 20, 2011.
- “Compressed Sensing to the Limits: Bounds, Algorithms, andWireless Applications,” University
of Michigan Electrical Engineering and Computer Science Seminar, March 31, 2009.
- “Sparsity Recovery: Limits, Algorithms and Wireless Applications,” DIMACS/DyDAn Working
Group on Streaming, Coding, and Compressive Sensing: Unifying Theory and Common
Applications to Sparse Signal/Data Analysis and Processing, New Brunswick, NJ, March 25–26, 2009.
(By invitation only workshop speaker and participant.)
- “Sparsity Pattern Recovery: Precisely Contrasting Thesholding, Lasso, and Maximum Likelihood,”
University of California at San Diego Information Theory and Applications Workshop,
February 8–13, 2009.
- “Random Access Channels and Sparsity Detection,” University of California at San Diego
Information Theory and Applications Workshop, February 8–13, 2009.
- American Institute of MathematicsWorkshop on Frames for the FiniteWorld: Sampling, Coding,
and Quantization, August 18–22, 2008 (invited participant).
- 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, UK.
- “Wavelet Denoising by Recursive Cycle Spinning,” DIMACSWorkshop on Source Coding and
Harmonic Analysis, May 9, 2003, New Brunswick, NJ.