2010
Anatoli Juditsky, Fatma Kilinc Karzan, Arkadi Nemirovski On Low Rank Matrix Approximations with Applications to Synthesis Problem in Compressed Sensing
Anatoli Juditsky, Fatma Kilinc Karzan, Arkadi Nemirovski L1 Minimization via Randomized 1st Order Algorithms
Itai Dattner, Alexander Goldenshluger, Anatoli Juditsky On Deconvolution of Distribution Functions
Anatoli Juditsky, Fatma Kilinc Karzan, Arkadi Nemirovski Guaranteed
bouns for L1-recovery
Anatoli Juditsky, Yuri
Nesterov
Primal-dual subgradient methods for minimizing uniformly
convex functions
Anatoli Juditsky, Arkadi Nemirovski First Order Methods for Nonsmooth Convex Large-Scale Optimization, I: General Purpose Methods (in Optimization for Machine Learning, Eds: S. Sra, S. Nowozin, S.J. Write, MIT Press, 2011)
Anatoli Juditsky, Arkadi Nemirovski First Order Methods for Nonsmooth Convex Large-Scale Optimization, II: Utilizing Problem's Structure (in Optimization for Machine Learning, Eds: S. Sra, S. Nowozin, S.J. Write, MIT Press, 2011)
2011
Elmar Diederichs, Anatoli Juditsky, Vladimir Spokoiny, Arkadi Nemirovski, Sparse Non Gaussian Component Analysis by Semidefinite Programming
Anatoli Juditsky, Fatma Kilinc Karzan, Arkadi Nemirovski, Boris Polyak, Accuracy guaranties for L1 recovery of block-sparse signals
Anatoli Juditsky, Fatma Kilinc Karzan, Arkadi Nemirovski, Boris Polyak, On the accuracy of l1-filtering of signals with block-sparse structure
2012
Anatoli Juditsky, Boris Polyak, Robust Eigenvector of a Stochastic Matrix with Application to PageRank
Anatoli Juditsky, Fatma Kilinc Karzan, Arkadi Nemirovski, On unified view of nullspace-type conditions for recoveries associated with general sparsity structures
2013
Anatoli Juditsky, Arkadi Nemirovski On Detecting Harmonic Oscillations
Bruce Cox, Anatoli Juditsky, Arkadi Nemirovski Dual subgradient algorithms for large-scale nonsmooth learning problems
Zaid Harchaoui, Anatoli Juditsky, Arkadi Nemirovski Conditional Gradient Algorithms for Norm-Regularized Smooth Convex Optimization