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An alternative point of view on Lepski's method

https://doi.org/10.1214/lnms/1215090065
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-1-4612-1880-7_4openalex-snapshot
From Model Selection to Adaptive Estimation
inferredcites →https://doi.org/10.1007/bf01199026openalex-snapshot
Minimax risk overl p -balls forl p -error
inferredcites →https://doi.org/10.1007/s004400050210openalex-snapshot
Risk bounds for model selection via penalization
inferredcites →https://doi.org/10.1007/s100970100031openalex-snapshot
Gaussian model selection
inferredcites →https://doi.org/10.1063/1.3057075openalex-snapshot
The Theory of Optimum Noise Immunity
inferredcites →https://doi.org/10.1080/01621459.1995.10476626openalex-snapshot
Adapting to Unknown Smoothness via Wavelet Shrinkage
inferredcites →https://doi.org/10.1088/0031-9112/20/9/025openalex-snapshot
The Theory of Optimum Noise Immunity
inferredcites →https://doi.org/10.1090/advsov/012/04openalex-snapshot
On problems of adaptive estimation in white Gaussian noise
inferredcites →https://doi.org/10.1093/biomet/68.1.45openalex-snapshot
An Optimal Selection of Regression Variables
inferredcites →https://doi.org/10.1093/biomet/81.3.425openalex-snapshot
Ideal Spatial Adaptation by Wavelet Shrinkage
inferredcites →https://doi.org/10.1137/1135065openalex-snapshot
On a Problem of Adaptive Estimation in Gaussian White Noise
inferredcites →https://doi.org/10.1137/1136085openalex-snapshot
Asymptotically Minimax Adaptive Estimation. I: Upper Bounds. Optimally Adaptive Estimates
inferredcites →https://doi.org/10.1201/b16414-10openalex-snapshot
Statistical Estimation: Asymptotic Theory
inferredcites →https://doi.org/10.1214/aos/1015957395openalex-snapshot
Adaptive estimation of a quadratic functional by model selection
inferredcites →https://doi.org/10.1214/aos/1024691478openalex-snapshot
Pointwise and sup-norm sharp adaptive estimation of functions on the Sobolev classes
inferredcites →https://doi.org/10.1214/aos/1069362731openalex-snapshot
Optimal spatial adaptation to inhomogeneous smoothness: an approach based on kernel estimates with variable bandwidth selectors
inferredcites →https://doi.org/10.2307/3318568openalex-snapshot
Neo-Classical Minimax Problems, Thresholding and Adaptive Function Estimation
inferredcites →https://doi.org/10.2307/3318752openalex-snapshot
On Global and Pointwise Adaptive Estimation

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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A Lepskiĭ-type stopping rule for the covariance estimation of multi-dimensional Lévy processes
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Nonparametric denoising of signals with unknown local structure, I: Oracle inequalities
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Classification with many classes: Challenges and pluses
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Adaptive nonparametric estimation for Lévy processes observed at low frequency
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Minimal penalty for Goldenshluger–Lepski method
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Adaptive and efficient estimation in the Gaussian sequence model
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Theory of Classification: a Survey of Some Recent Advances
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Adaptive tests for periodic signal detection with applications to laser vibrometry
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Optimal Sparse Singular Value Decomposition for High-Dimensional High-Order Data
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Uniform Inference for Kernel Density Estimators with Dyadic Data
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The generalized orthogonal Procrustes problem in the high noise regime
inferred← citeshttps://doi.org/10.1093/imaiai/iaad003openalex-snapshot
Sparse confidence sets for normal mean models
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Inference with Mondrian random forests
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Limits and security of free-space quantum communications
inferred← citeshttps://doi.org/10.1109/allerton.2018.8635825openalex-snapshot
Parameter Estimation in Gaussian Mixture Models with Malicious Noise, without Balanced Mixing Coefficients
inferred← citeshttps://doi.org/10.1109/globecom42002.2020.9348157openalex-snapshot
Energy-efficiency of Massive Random Access with Individual Codebook
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Information-theoretic bounds on sparsity recovery in the high-dimensional and noisy setting
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High-dimensional analysis of semidefinite relaxations for sparse principal components
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Centralized Versus Decentralized Detection of Attacks in Stochastic Interconnected Systems
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Energy Efficient Coded Random Access for the Wireless Uplink
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Information-Theoretic Limits on Sparsity Recovery in the High-Dimensional and Noisy Setting
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Information-Theoretic Limits on Sparse Signal Recovery: Dense versus Sparse Measurement Matrices
inferred← citeshttps://doi.org/10.1109/tit.2014.2381241openalex-snapshot
Optimal Feature Selection in High-Dimensional Discriminant Analysis
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Information-Theoretic Bounds and Phase Transitions in Clustering, Sparse PCA, and Submatrix Localization
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Sub-Linear Time Support Recovery for Compressed Sensing Using Sparse-Graph Codes
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Fundamental Limits of Many-User MAC With Finite Payloads and Fading
inferred← citeshttps://doi.org/10.1109/tit.2022.3220261openalex-snapshot
Energy Efficiency of Massive Random Access in MIMO Quasi-Static Rayleigh Fading Channels With Finite Blocklength
inferred← citeshttps://doi.org/10.1109/tit.2025.3618595openalex-snapshot
Pearson Chi-Squared Conditional Randomization Test
inferred← citeshttps://doi.org/10.1109/tsp.2025.3583895openalex-snapshot
Efficient Off-Grid Bayesian Parameter Estimation for Kronecker-Structured Signals
inferred← citeshttps://doi.org/10.1111/rssb.12447openalex-snapshot
High-Dimensional, Multiscale Online Changepoint Detection
inferred← citeshttps://doi.org/10.1111/stan.12103openalex-snapshot
Spline regression for hazard rate estimation when data are censored and measured with error
inferred← citeshttps://doi.org/10.1184/r1/6476276openalex-snapshot
Recovering Block-structured Activations Using Compressive Measurements
inferred← citeshttps://doi.org/10.1214/009053604000000085openalex-snapshot
Confidence balls in Gaussian regression
inferred← citeshttps://doi.org/10.1214/009053604000000896openalex-snapshot
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inferred← citeshttps://doi.org/10.1214/07-aos500openalex-snapshot
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inferred← citeshttps://doi.org/10.1214/07-ejs127openalex-snapshot
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inferred← citeshttps://doi.org/10.1214/08-aos664openalex-snapshot
High-dimensional analysis of semidefinite relaxations for sparse principal components
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Minimax risks for sparse regressions: Ultra-high dimensional phenomenons
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Nearly optimal minimax estimator for high-dimensional sparse linear regression
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Anisotropic function estimation using multi-bandwidth Gaussian processes
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Adaptive density estimation in deconvolution problems with unknown error distribution
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Family-Wise Separation Rates for multiple testing
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Statistical properties of convex clustering
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Tail index estimation, concentration and adaptivity
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Minimax goodness-of-fit testing in ill-posed inverse problems with partially unknown operators
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Multidimensional two-component Gaussian mixtures detection
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Recovering block-structured activations using compressive measurements
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Bootstrap tuning in Gaussian ordered model selection
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Minimax Euclidean separation rates for testing convex hypotheses in $\mathbb{R}^{d}$
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On the post selection inference constant under restricted isometry properties
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An optimal statistical and computational framework for generalized tensor estimation
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Minimax adaptive estimation in manifold inference
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Scale calibration for high-dimensional robust regression
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Nonregular and minimax estimation of individualized thresholds in high dimension with binary responses
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Consistency of invariance-based randomization tests
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Two-sample testing of high-dimensional linear regression coefficients via complementary sketching
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Consistency of a range of penalised cost approaches for detecting multiple changepoints
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Off-policy evaluation in partially observed Markov decision processes under sequential ignorability
inferred← citeshttps://doi.org/10.1214/24-ejs2294openalex-snapshot
Efficient sparsity adaptive changepoint estimation
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Bayesian one- and two-sided inference on the local effective dimension
inferred← citeshttps://doi.org/10.1214/aos/1028674843openalex-snapshot
Oracle inequalities for inverse problems
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Adaptive tests of linear hypotheses by model selection
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On Binscatter
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Aggregated kernel based tests for signal detection in a regression model
inferred← citeshttps://doi.org/10.13140/rg.2.2.26552.24325openalex-snapshot
Adaptivity for Regularized Kernel Methods by Lepskii's Principle
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Adaptive Bayesian Estimation in Indirect Gaussian Sequence Space Models
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Changepoint detection for data intensive settings
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Empirical Bayes Estimators for High-Dimensional Sparse Vectors
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High-Dimensional, Multiscale Online Changepoint Detection
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Resampling-based tuning of ordered model selection
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Nonparametric adaptive estimation of linear functionals for low frequency observed Lévy processes
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Anti-concentration and honest, adaptive confidence bands
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Anti-concentration and honest, adaptive confidence bands
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Sharp Boundary Laws for Outcome-conditional Dark Mass in the Multi-observation Model
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Adaptive estimation of marginal random-effects densities in linear mixed-effects models
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Testing the regularity of a smooth signal
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Bump detection in heterogeneous Gaussian regression
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The Goldenshluger–Lepski method for constrained least-squares estimators over RKHSs
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Distributed function estimation: Adaptation using minimal communication
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Joint Optimization and Variable Selection of High-dimensional Gaussian Processes
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Rate Optimal Denoising of Simultaneously Sparse and Low Rank Matrices
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Lepski's Method and Adaptive Estimation of Nonlinear Integral Functionals of Density
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SPRIGHT: A Fast and Robust Framework for Sparse Walsh-Hadamard Transform
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Excess Optimism: How Biased is the Apparent Error of an Estimator Tuned by SURE?
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Minimax Euclidean Separation Rates for Testing Convex Hypotheses in $\mathbb{R}^d$
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Optimal Sparse Singular Value Decomposition for High-dimensional High-order Data
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Learning Some Popular Gaussian Graphical Models without Condition Number Bounds
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On the optimality of kernels for high-dimensional clustering
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Adaptive minimax testing in inverse Gaussian sequence space models
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Adaptive Estimator Selection for Off-Policy Evaluation
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Score-Based Change Detection for Gradient-Based Learning Machines
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Differentially private methods for managing model uncertainty in linear regression models
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Confidence sets for model selection by F -testing
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High dimensional multiple means estimation and testing with applications to machine learning
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Modèle de régression pour des données non-Euclidiennes en grande dimension. Application à la classification de taxons en anatomie computationnelle.
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Stochastic approximation in Hilbert spaces
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