Name
Matus Telgarsky

Email
mtelgars at cs dot ucsd dot edu

Locations
2013 - (?). Postdoc in Statistics, Rutgers University. Host: Tong Zhang.

2013 - (?). Consultant at MSR NYC. Host: John Langford.

2007 - 2013. PhD in Computer Science, UCSD. Advisor: Sanjoy Dasgupta.

2004 - 2007. BS in Computer Science & Discrete Math, CMU.

2001 - 2003. Diploma in Violin Performance, Juilliard.

Postprints
Moment-based Uniform Deviation Bounds for \(k\)-means and Friends. (With Sanjoy Dasgupta.) [pdf] [arXiv] [poster] Boosting with the Logistic Loss is Consistent. [arXiv] [short video] Margins, Shrinkage, and Boosting. [arXiv] [video] Agglomerative Bregman Clustering. (With Sanjoy Dasgupta.) [pdf] [short video] A Primal-Dual Convergence Analysis of Boosting. [arXiv] [jmlr] Steepest Descent Analysis for Unregularized Linear Prediction with Strictly Convex Penalties. [pdf] [video] The Fast Convergence of Boosting. [pdf] Hartigan's Method: \(k\)-means without Voronoi. (With Andrea Vattani.) [pdf] [old javscript demo] Signal decomposition using multiscale admixture models. (With John Lafferty.)

Notes
Dirichlet draws are sparse with high probability. [arXiv]

Preprints
Blackwell Approachability and Minimax Theory. (2011.) [arXiv]

Central Binomial Tail Bounds. (2009.) [arXiv]

Ph.D. Thesis
Duality and Data Dependence in Boosting. (2013.) [pdf]