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Prediction in Functional Linear Regression

The Annals of statistics, 2006-10, Vol.34 (5), p.2159-2179

2006

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Properties of Principal Component Methods for Functional and Longitudinal Data Analysis

The Annals of statistics, 2006-06, Vol.34 (3), p.1493-1517

2006

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A hypothesis about the rate of global convergence for optimal methods (Newtons type) in smooth convex optimization

Kompʹûternye issledovaniâ i modelirovanie (Online), 2018-06, Vol.10 (3), p.305-314

2018

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Some properties of modified Szász–Mirakyan operators in polynomial spaces via the power summability method

Journal of applied analysis, 2020-06, Vol.26 (1), p.79-90

Braha, Naim L.

2020

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NONASYMPTOTIC CONVERGENCE ANALYSIS FOR THE UNADJUSTED LANGEVIN ALGORITHM

The Annals of applied probability, 2017-06, Vol.27 (3), p.1551-1587

2017

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High-dimensional Bayesian inference via the unadjusted Langevin algorithm

Bernoulli : official journal of the Bernoulli Society for Mathematical Statistics and Probability, 2019-11, Vol.25 (4A)

2019

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On the Convergence of Block Coordinate Descent Type Methods

SIAM journal on optimization, 2013-01, Vol.23 (4), p.2037-2060

2013

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Analysis of a random forests model

Journal of machine learning research, 2012-04, Vol.13, p.1063-1095

Biau, Gérard

2012

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Stability Problems for Stochastic Models: Theory and Applications II

2022

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Study of convergence for a new iterative rate method

AIP Conference Proceedings, 2023, Vol.2834 (1)

2023

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Function values are enough for L2-approximation: Part II

Journal of Complexity, 2021-10, Vol.66, p.101569, Article 101569

2021

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STRONG IDENTIFIABILITY AND OPTIMAL MINIMAX RATES FOR FINITE MIXTURE ESTIMATION

The Annals of statistics, 2018-12, Vol.46 (6A), p.2844-2870

2018

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A Note on Sampling Recovery of Multivariate Functions in the Uniform Norm

SIAM journal on numerical analysis, 2022-06, Vol.60 (3), p.1363-1384

2022

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Central limit theorem with rate of convergence under sublinear expectations

Stochastic processes and their applications, 2024-06, Vol.172, p.104353, Article 104353

2024

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Uniform regularity for a Keller–Segel–Navier–Stokes system

Applied mathematics letters, 2020-09, Vol.107, p.106476, Article 106476

2020

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Equivalence of approximation by convolutional neural networks and fully-connected networks

Proceedings of the American Mathematical Society, 2020-04, Vol.148 (4), p.1567-1581

2020

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ON DEEP LEARNING AS A REMEDY FOR THE CURSE OF DIMENSIONALITY IN NONPARAMETRIC REGRESSION

The Annals of statistics, 2019-08, Vol.47 (4), p.2261-2285

2019

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A sharp upper bound for sampling numbers in L2

Applied and computational harmonic analysis, 2023-03, Vol.63, p.113-134

2023

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Exponential convergence of distributed primal–dual convex optimization algorithm without strong convexity

Automatica (Oxford), 2019-07, Vol.105, p.298-306

2019

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Greedy Quasi-Newton Methods with Explicit Superlinear Convergence

SIAM journal on optimization, 2021-01, Vol.31 (1), p.785-811

2021

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Convergence Analysis of Machine Learning Algorithms for the Numerical Solution of Mean Field Control and Games I: The Ergodic Case

SIAM journal on numerical analysis, 2021-01, Vol.59 (3), p.1455-1485

2021

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A strong uniform approximation of fractional Brownian motion by means of transport processes

Stochastic processes and their applications, 2009-10, Vol.119 (10), p.3435-3452

2009

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On the rate of convergence of fully connected deep neural network regression estimates

The Annals of statistics, 2021-08, Vol.49 (4), p.2231

2021

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A Constrained ℓ1 Minimization Approach to Sparse Precision Matrix Estimation

Journal of the American Statistical Association, 2011-06, Vol.106 (494), p.594-607

2011

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New higher order Haar wavelet method: Application to FGM structures

Composite structures, 2018-10, Vol.201, p.72-78

2018

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Prediction in Functional Linear Regression

Properties of Principal Component Methods for Functional and Longitudinal Data Analysis

A hypothesis about the rate of global convergence for optimal methods (Newtons type) in smooth convex optimization

Some properties of modified Szász–Mirakyan operators in polynomial spaces via the power summability method

NONASYMPTOTIC CONVERGENCE ANALYSIS FOR THE UNADJUSTED LANGEVIN ALGORITHM

High-dimensional Bayesian inference via the unadjusted Langevin algorithm

On the Convergence of Block Coordinate Descent Type Methods

Analysis of a random forests model

Stability Problems for Stochastic Models: Theory and Applications II

Study of convergence for a new iterative rate method

Function values are enough for L2-approximation: Part II

STRONG IDENTIFIABILITY AND OPTIMAL MINIMAX RATES FOR FINITE MIXTURE ESTIMATION

A Note on Sampling Recovery of Multivariate Functions in the Uniform Norm

Central limit theorem with rate of convergence under sublinear expectations

Uniform regularity for a Keller–Segel–Navier–Stokes system

Equivalence of approximation by convolutional neural networks and fully-connected networks

ON DEEP LEARNING AS A REMEDY FOR THE CURSE OF DIMENSIONALITY IN NONPARAMETRIC REGRESSION

A sharp upper bound for sampling numbers in L2

Exponential convergence of distributed primal–dual convex optimization algorithm without strong convexity

Greedy Quasi-Newton Methods with Explicit Superlinear Convergence

Convergence Analysis of Machine Learning Algorithms for the Numerical Solution of Mean Field Control and Games I: The Ergodic Case

A strong uniform approximation of fractional Brownian motion by means of transport processes

On the rate of convergence of fully connected deep neural network regression estimates

A Constrained ℓ1 Minimization Approach to Sparse Precision Matrix Estimation

New higher order Haar wavelet method: Application to FGM structures

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