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)