Publications
Book
Anatoli Juditsky, Arkadi Nemirovski. Statistical Inference via Convex Optimization
2013
Elmar Diederichs, Anatoli Juditsky, Arkadi Nemirovski, V Spokoiny. Sparse non Gaussian component analysis by semidefinite programming
Anatoli Juditsky, Fatma Kilinc Karzan, Arkadi Nemirovski. Randomized first order algorithms with applications to ℓ1-minimization
Anatoli Juditsky, Arkadi Nemirovski. Solving Variational Inequalities with Monotone Operators on Domains Given by Linear Minimization Oracles
2014
Bruce Cox, Anatoli Juditsky, Arkadi Nemirovski. Dual subgradient algorithms for large-scale nonsmooth learning problems
Anatoli Juditsky, Fatma Kilinc Karzan, Arkadi Nemirovski. On a unified view of nullspace-type conditions for recoveries associated with general sparsity structures
Anatoli Juditsky, Yuri Nesterov. Deterministic and stochastic primal-dual subgradient algorithms for uniformly convex minimization
2015
Alexander Goldenshluger, Anatoli Juditsky, Arkadi Nemirovski. Hypothesis Testing by Convex Optimization (discussion paper)
Alexander Goldenshluger, Anatoli Juditsky, Arkadi Nemirovski. Rejoinder of “Hypothesis testing by convex optimization”
Anatoli Juditsky, Arkadi Nemirovski. On sequential hypotheses testing via convex optimization
Zaid Harchaoui, Anatoli Juditsky, Arkadi Nemirovski. Conditional Gradient Algorithms for Norm-Regularized Smooth Convex Optimization
Anatoli Juditsky, Arkadi Nemirovski. On Detecting Harmonic Oscillations
Niao He, Anatoli Juditsky, Arkadi Nemirovski. Mirror Prox Algorithm for Multi-Term Composite Minimization and Alternating Directions
Zaid Harchaoui, Anatoli Juditsky, Arkadi Nemirovski, Dmitri Ostrovsky. Adaptive Recovery of Signals by Convex Optimization
2016
Anatoli Juditsky, Arkadi Nemirovski. Hypothesis Testing via Affine Detectors
Zaid Harchaoui, Anatoli Juditsky, Arkadi Nemirovski, Dmitri Ostrovsky. Structure-blind signal recovery
Anatoli Juditsky, Arkadi Nemirovski. Solving Variational Inequalities with Monotone Operators on Domains Given by Linear Minimization Oracles
2017
Bruce Cox, Anatoli Juditsky, Arkadi Nemirovski. Decomposition techniques for bilinear saddle point problems and variational inequalities with affine monotone operators
Vincent Guigues, Anatoli Juditsky, Arkadi Nemirovski. Non-asymptotic confidence bounds for the optimal value of a stochastic program
Yao Cao, Vincent Guigues, Anatoli Juditsky, Arkadi Nemirovski, Yao Xie. Change detection via affine and quadratic detectors
2018
Anatoli Juditsky, Arkadi Nemirovski. Near-optimality of linear recovery in Gaussian observation scheme under l_2-loss
Anatoli Juditsky, Arkadi Nemirovski. Near-Optimality of Linear Recovery from Indirect Observations
2019
Vincent Guigues, Anatoli Juditsky, Arkadi Nemirovski. Hypothesis testing via Euclidean separation
Anatoli Juditsky, Arkadi Nemirovski. Near-optimal recovery of linear and N-convex functions on unions of convex sets
Anatoli Juditsky, Arkadi Nemirovski. Signal Recovery by Stochastic Optimization
Anatoli Juditsky, Alexander Nazin, Arkadi Nemirovski, Alexander Tsybakov. Algorithms of robust stochastic optimization based on mirror descent method
Anatoli Juditsky, Arkadi Nemirovski. Estimating Linear and Quadratic forms via Indirect Observations
Anatoli Juditsky, Arkadi Nemirovski. On Polyhedral Estimation of Signals via Indirect Observations
2020
Vincent Guigues, Anatoli Juditsky, Arkadi Nemirovski. Constant Depth Decision Rules for multistage optimization under uncertainty
Anatoli Juditsky, Arkadi Nemirovski, Liyan Xie, Yao Xie. Convex parameter recovery for interacting Marked processes
Anatoli Juditsky, Andrei Kulunchakov, Hlib Tsyntseus, Sparse recovery by reduced variance stochastic approximation
2021
Anatoli Juditsky, Arkadi Nemirovski. On Well-Structured Convex-Concave Saddle Point Problems and Variational Inequalities with Monotone Operators
Anatoli Juditsky, Arkadi Nemirovski. Aggregating estimates by convex optimization
Anatoli Juditsky, Georgios Kotsalis, Arkadi Nemirovski. Tight computationally efficient approximation of matrix norms with applications
2022
Anatoli Juditsky, Joon Kwon, Eric Moulines. Unifying mirror descent and dual averaging
Anatoli Juditsky, Arkadi Nemirovski. On Design of Polyhedral Estimates in Linear Inverse Problems
Zaid Harchaoui, Anatoli Juditsky, Arkadi Nemirovski, Dmitri Ostrovsky. Adaptive Denoising of Signals with Local Shift-Invariant Structure
Anatoli Juditsky, Arkadi Nemirovski. Aggregating regular norms
Yannis Bekry, Sasila Ilandarideva, Anatoli Juditsky, Vianney Perchet. Stochastic Mirror Descent for Large-Scale Sparse Recovery
2023
Anatoli Juditsky, Arkadi Nemirovski, Mikhail Zibulevsky. Radiation design in computed tomography via convex optimization
Yannis Bekry, Anatoli Juditsky, Arkadi Nemirovski On Robust Recovery of Signals from Indirect Observations
Sasila Ilandarideva, Anatoli Juditsky, Guanghui Lan, Tianjiao Li Accelerated stochastic approximation with state-dependent noise
Anatoli Juditsky, Arkadi Nemirovski, Yao Xie, Chen Xu. “Generalized” generalized linear models: Convex estimation and online bounds
Some hard to find oldies
Anatoli Juditsky. Wavelete Estimators: Adapting to Unknown Smoothness (1994)
Anatoli Juditsky, Oleg Lepski. Confidence intervals for adaptive regression estimation (1998)
Anatoli Juditsky, Sophie Lambert-Lacroix. On nonparametric confidence set estimation (2003)