Michael B. McCoy

About me

I am a Postdoctoral Scholar in Computing and Mathematical Sciences working with Joel Tropp.

Curriculum Vitae

Research summary

My work explores computational methods for extracting information from data. I aim to provide quantitatively precise and rigorous guarantees for computational inference procedures. These strong guarantees are critical for engineers, statisticians, and others in data-intensive sciences who need to design systems or analyze experimental results. I approach these problems by exploring relationships between optimization, geometry, probability, and statistics.

Research vignettes

Demixing superimposed signals

Robust principal component analysis

News and updates

March 28, 2014: Our paper From Steiner formulas for cones to concentration of intrinsic volumes has been accepted to Discrete and Computational Geometry.

January 9, 2014: My paper Sharp recovery bounds for convex demixing, with applications has been accepted to JoFoCM.

January 7, 2014: Want to plot your own phase transitions? Try out my statistical dimension code!

November 1, 2013: We have a new tutorial article on convex methods for signal separation: Convexity in source separation: Models, geometry, and algorithms.

September 30, 2013: A new result on the limits of convex methods for demixing signals: The achievable performance of convex demixing.

August 26, 2013: Our latest paper is now available: From Steiner formulas for cones to concentration of intrinsic volumes.

June 14, 2013: I recieved the W.P. Carey & Co. Inc. Prize in Applied & Computational Mathematics for an outstanding doctoral dissertation.

May 23, 2013: My thesis is now available: A geometric analysis of convex demixing.

May 13, 2013: I successfully defended my Ph.D. thesis! The final copy will be available on this page soon.

March 26, 2013: Another one out: D. Amelunxen, M. Lotz, M.B. McCoy, and J.A. Tropp, Living on the edge: A geometric theory of phase transitions in convex optimization [arXiv:1303.6672]

May 8, 2012: Our deconvolution paper is available! M.B. McCoy and J.A. Tropp, Sharp bounds for convex deconvolution, with applications. 2012. preprint.

February 23, 2012: Our newest paper is out in the wild! Check it out. G. Lerman, M. McCoy, J.A. Tropp, and T. Zhang, Robust computation of linear models, or How to find a needle in a haystack . 2012. preprint.

September 14, 2011: Our paper "Two Proposals for Robust PCA using Semidefinite Programming" will appear in the Electronic Journal of Statistics (open-access).

August 11, 2011: I've updated my robust PCA code to reflect a revision in the paper. See here.

June 27—30, 2011: I'm attending SPARS'11 in Edinburgh, Scotland, where I'm presenting a talk titled "Two Proposals for Robust PCA" based on the pre-print here. The code associated with our work is here, and the slides are available here.

June 15, 2011: I've had to migrate this website to the new CMS server, as the old ACM department is no more. Please let me know if you find any broken links or other issues.

September 13—December 17, 2010: I'm spending much of my time at UCLA for the Modern Trends in Optimization and Its Application workshop.

June 7, 2010: Added a section about teaching since a couple of us are running a self-taught algebraic geometry course.

April 5, 2010: I added a makefile for LaTeX files to my code directory that I've been using for some time in case anyone else finds it useful.

March 18, 2010: I have uploaded a tar.gz file containing a Matlab implementation of the CoSaMP algorithm for compressed sensing. See the code directory for more details.

Jan. 29, 2010: I gave a talk on the maxcut semidefinite relaxation of Goemans and Williamson titled "Relax and Do Something Random" at the ACM^T hour.

Last Modified: Friday, 28-Mar-2014 12:06:52 PDT

Valid HTML 4.01 Transitional