Finite sample properties of parametric MMD estimation: robustness to misspecification and dependence
From MaRDI portal
Publication:2073208
DOI10.3150/21-BEJ1338MaRDI QIDQ2073208
Pierre Alquier, Badr-Eddine Chérief-Abdellatif
Publication date: 1 February 2022
Published in: Bernoulli (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1912.05737
Related Items (4)
A Bayesian approach to (online) transfer learning: theory and algorithms ⋮ Discrepancy-based inference for intractable generative models using quasi-Monte Carlo ⋮ Estimation of Copulas via Maximum Mean Discrepancy ⋮ Finite sample properties of parametric MMD estimation: robustness to misspecification and dependence
Cites Work
- Large Sample Properties of Generalized Method of Moments Estimators
- A Kernel Multiple Change-point Algorithm via Model Selection
- Geometric median and robust estimation in Banach spaces
- A new method for estimation and model selection: \(\rho\)-estimation
- Sub-Gaussian mean estimators
- On McDiarmid's concentration inequality
- Weakly dependent functional data
- SPADES and mixture models
- Rates of convergence of minimum distance estimators and Kolmogorov's entropy
- Random generation of combinatorial structures from a uniform distribution
- The space complexity of approximating the frequency moments
- Mixing: Properties and examples
- A new weak dependence condition and applications to moment inequalities
- Inconsistency of Bayesian inference for misspecified linear models, and a proposal for repairing it
- Optimal Kullback-Leibler aggregation in mixture density estimation by maximum likelihood
- Robust dimension-free Gram operator estimates
- Consistency of variational Bayes inference for estimation and model selection in mixtures
- Robust covariance and scatter matrix estimation under Huber's contamination model
- Computational aspects of fitting mixture models via the expectation-maximization algorithm
- Challenging the empirical mean and empirical variance: a deviation study
- The consistency of posterior distributions in nonparametric problems
- Regression depth and center points.
- Rho-estimators revisited: general theory and applications
- Finite sample properties of parametric MMD estimation: robustness to misspecification and dependence
- Robust statistical learning with Lipschitz and convex loss functions
- Mean estimation with sub-Gaussian rates in polynomial time
- Some theoretical properties of GANs
- Robust classification via MOM minimization
- Risk minimization by median-of-means tournaments
- Multidimensional linear functional estimation in sparse Gaussian models and robust estimation of the mean
- Mean estimation and regression under heavy-tailed distributions: A survey
- Optimal estimation and rank detection for sparse spiked covariance matrices
- Robust PCA and pairs of projections in a Hilbert space
- Model selection via testing: an alternative to (penalized) maximum likelihood estimators.
- Convergence of estimates under dimensionality restrictions
- Weak dependence. With examples and applications.
- Concentration Inequalities
- Hilbert space embeddings and metrics on probability measures
- Asymptotic Theory of Weakly Dependent Random Processes
- A CENTRAL LIMIT THEOREM AND A STRONG MIXING CONDITION
- The Minimum Distance Method
- Robust Stochastic Approximation Approach to Stochastic Programming
- Minimum Distance and Robust Estimation
- Inégalités de Hoeffding pour les fonctions lipschitziennes de suites dépendantes
- Asymptotic Statistics
- Kernel Mean Embedding of Distributions: A Review and Beyond
- Robust Estimators in High-Dimensions Without the Computational Intractability
- Minimax Estimation of Kernel Mean Embeddings
- [https://portal.mardi4nfdi.de/wiki/Publication:4743580 Approximation dans les espaces m�triques et th�orie de l'estimation]
- Density estimation with quadratic loss: a confidence intervals method
- Robust moment estimation and improved clustering via sum of squares
- List-decodable robust mean estimation and learning mixtures of spherical gaussians
- Efficient Algorithms and Lower Bounds for Robust Linear Regression
- Sparse Density Estimation with ℓ1 Penalties
- Robust Estimation of a Location Parameter
- On the Assumptions Used to Prove Asymptotic Normality of Maximum Likelihood Estimates
- Combinatorial methods in density estimation
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
This page was built for publication: Finite sample properties of parametric MMD estimation: robustness to misspecification and dependence