2026 Vladimir Spokoiny: Mathematics Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Mathematics	43	1694	1466	99	88	202	7807

Discipline name

D-Index

World Ranking

Current World Ranking

National Ranking

Current National Ranking

Publications

Citations

Mathematics

1694

1466

202

7807

Overview

Vladimir Spokoiny is affiliated with the Weierstrass Institute for Applied Analysis and Stochastics in Germany. Their research spans key domains in mathematics and computer science, with a focus on statistical and computational methods.

The main fields of study in Vladimir Spokoiny's work include:

Mathematics
Computer Science

Their research explores various subfields such as:

Statistics and Probability
Artificial Intelligence
Computational Mechanics
Computational Theory and Mathematics
Numerical Analysis

Main topics covered in Vladimir Spokoiny's publications are:

Statistical Methods and Inference
Sparse and Compressive Sensing Techniques
Markov Chains and Monte Carlo Methods
Statistical Methods and Bayesian Inference
Stochastic Gradient Optimization Techniques
Optimization and Variational Analysis
Gaussian Processes and Bayesian Inference

Vladimir Spokoiny has published extensively, contributing to journals and proceedings frequently. Prominent venues for their work include:

arXiv (Cornell University)
Bernoulli
Communications in Mathematical Sciences
The Annals of Applied Probability
IFAC-PapersOnLine

Recent papers authored or co-authored by Vladimir Spokoiny include:

Dimension Free Nonasymptotic Bounds on the Accuracy of High-Dimensional Laplace Approximation, 2023, SIAM/ASA Journal on Uncertainty Quantification
Sharper dimension-free bounds on the Frobenius distance between sample covariance and its expectation, 2025, Bernoulli
Accelerated gradient methods with absolute and relative noise in the gradient, 2023, Optimization Methods & Software
On the line-search gradient methods for stochastic optimization, 2020, IFAC-PapersOnLine
Statistical inference for Bures-Wasserstein barycenters, 2021, The Annals of Applied Probability

Frequent collaboration is a characteristic of Vladimir Spokoiny's work. Common coauthors include:

Nikita Puchkin
Alexandra Suvorikova
Alexander Gasnikov
Pavel Dvurechensky
Denis Belomestny

Best Publications

Random Gradient-Free Minimization of Convex Functions

Yurii Nesterov;Vladimir Spokoiny

1021
Citations
An Adaptive, Rate-Optimal Test of a Parametric Mean-Regression Model Against a Nonparametric Alternative

Joel L. Horowitz;Vladimir G. Spokoiny

465
Citations
Optimal spatial adaptation to inhomogeneous smoothness: an approach based on kernel estimates with variable bandwidth selectors

O. V. Lepski;E. Mammen;V. G. Spokoiny

401
Citations
Direct estimation of the index coefficient in a single-index model

Marian Hristache;Anatoli Juditsky;Vladimir Spokoiny

378
Citations
Adaptive weights smoothing with applications to image restoration

J. Polzehl;V. G. Spokoiny

314
Citations
Adaptive hypothesis testing using wavelets

V. G. Spokoiny

300
Citations
Optimal pointwise adaptive methods in nonparametric estimation

O. V. Lepski;V. G. Spokoiny

271
Citations
Propagation-Separation Approach for Local Likelihood Estimation

Jörg Polzehl;Vladimir Spokoiny

254
Citations
Multiscale testing of qualitative hypotheses

Lutz Dümbgen;Vladimir G. Spokoiny

250
Citations
Structure Adaptive Approach for Dimension Reduction

Marian Hristache;Anatoli Juditsky;Jörg Polzehl;Vladimir Spokoiny

220
Citations
Statistical inference for time-inhomogeneous volatility models

Danilo Mercurio;Vladimir G. Spokoiny

199
Citations
Parametric estimation. Finite sample theory

Vladimir Spokoiny

161
Citations
Multiscale local change point detection with applications to value-at-risk

Vladimir Spokoiny

154
Citations
ESTIMATION OF A FUNCTION WITH DISCONTINUITIES VIA LOCAL POLYNOMIAL FIT WITH AN ADAPTIVE WINDOW CHOICE

Vladimir G. Spokoiny

153
Citations
Inhomogeneous Dependence Modeling with Time-Varying Copulae

Enzo Giacomini;Wolfgang Härdle;Vladimir Spokoiny

148
Citations
Minimax nonparametric hypothesis testing: the case of an inhomogeneous alternative

Oleg V. Lepski;Vladimir G. Spokoiny

134
Citations
On estimation of the Lr norm of a regression function

O. Lepski;A. Nemirovski;V. Spokoiny

119
Citations
Analyzing fMRI experiments with structural adaptive smoothing procedures

Karsten Tabelow;Jörg Polzehl;Henning U. Voss;Vladimir G. Spokoiny

108
Citations
In Search of Non-Gaussian Components of a High-Dimensional Distribution

Gilles Blanchard;Gilles Blanchard;Motoaki Kawanabe;Masashi Sugiyama;Masashi Sugiyama;Vladimir Spokoiny

98
Citations
Testing a Statistical Hypothesis

Vladimir Spokoiny;Thorsten Dickhaus

5
Citations

Frequent Co-Authors

Wolfgang Karl Härdle Humboldt-Universität zu Berlin

Anatoli Juditsky Grenoble Alpes University

Klaus-Robert Müller Technical University of Berlin

Masashi Sugiyama RIKEN

Motoaki Kawanabe Advanced Telecommunications Research Institute International

Yurii Nesterov Université Catholique de Louvain

Arkadi Nemirovski Georgia Institute of Technology

Albert N. Shiryaev Steklov Mathematical Institute

Friedrich Götze Bielefeld University

Enno Mammen Heidelberg University

External Links

Personal website of Vladimir Spokoiny Google Scholar page

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