Conference & journal
Rate of Price Discovery in Iterative Combinatorial Auctions.
Jacob Abernethy, Sébastien Lahaie, Matus Telgarsky.
[arXiv] Benefits of Depth in Neural Networks.
Matus Telgarsky.
[arXiv] [10min video] Convex Risk Minimization and Conditional Probability Estimation.
Matus Telgarsky, Miroslav Dudík, Robert Schapire.
[arXiv] [short video] [poster] Scalable Nonlinear Learning with Adaptive Polynomial Expansions.
Alekh Agarwal, Alina Beygelzimer, Daniel Hsu, John Langford, Matus Telgarsky.
[arXiv] Tensor decompositions for learning latent variable models.
Anima Anandkumar, Rong Ge, Daniel Hsu, Sham M. Kakade, Matus Telgarsky.
[arXiv] [jmlr] Moment-based Uniform Deviation Bounds for \(k\)-means and Friends.
Matus Telgarsky, Sanjoy Dasgupta.
[pdf] [arXiv] [poster] Boosting with the Logistic Loss is Consistent.
Matus Telgarsky.
[arXiv] [short video] Margins, Shrinkage, and Boosting.
Matus Telgarsky.
[arXiv] [video] Agglomerative Bregman Clustering.
Matus Telgarsky, Sanjoy Dasgupta.
[pdf] [short video] A Primal-Dual Convergence Analysis of Boosting.
Matus Telgarsky.
[arXiv] [jmlr] The Fast Convergence of Boosting.
Matus Telgarsky.
[pdf] Hartigan's Method: \(k\)-means without Voronoi.
Matus Telgarsky, Andrea Vattani.
[pdf] [old javascript demo] Signal decomposition using multiscale admixture models.
Matus Telgarsky, John Lafferty.

Representation results & algorithms for deep feedforward networks.
Jacob Abernethy, Alex Kulesza, Matus Telgarsky.
[pdf] Rate of price discovery in iterative combinatorial auctions.
Jacob Abernethy, Sébastien Lahaie, Matus Telgarsky.
[arXiv] Steepest descent analysis for unregularized linear prediction with strictly convex penalties.
Matus Telgarsky.
[pdf] [video]

Representation Benefits of Deep Feedforward Networks. [arXiv]
Dirichlet draws are sparse with high probability. [arXiv]

Greedy bi-criteria approximations for \(k\)-medians and \(k\)-means. (2016, with Daniel Hsu.) [arXiv]

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

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

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