Weighted discrepancy principle and optimal adaptivity in Poisson inverse problems
From MaRDI portal
Publication:6634800
DOI10.30757/alea.v21-43MaRDI QIDQ6634800
Publication date: 8 November 2024
Published in: ALEA. Latin American Journal of Probability and Mathematical Statistics (Search for Journal in Brave)
Nonparametric estimation (62G05) Estimation and detection in stochastic control theory (93E10) Numerical solutions of ill-posed problems in abstract spaces; regularization (65J20) Inverse problems for integral equations (45Q05)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Poisson intensity estimation for the Spektor-Lord-Willis problem using a wavelet shrinkage approach
- Probability in Banach spaces. Isoperimetry and processes
- B-splines and discretization in an inverse problem for Poisson processes
- Beyond the Bakushinkii veto: regularising linear inverse problems without knowing the noise distribution
- Poisson inverse problems
- An adaptive wavelet shrinkage approach to the Spektor-Lord-Willis problem
- Discretization effects in statistical inverse problems
- The law of large numbers and the central limit theorem in Banach spaces
- Early stopping for statistical inverse problems via truncated SVD estimation
- Morozov principle for Kullback-Leibler residual term and Poisson noise
- Asymptotic confidence bands in the Spektor-Lord-Willis problem via kernel estimation of intensity derivative
- Towards adaptivity via a new discrepancy principle for Poisson inverse problems
- Smoothed residual stopping for statistical inverse problems via truncated SVD estimation
- Nonparametric intensity estimation from noisy observations of a Poisson process under unknown error distribution
- A course on point processes
- Inverse problems with Poisson data: statistical regularization theory, applications and algorithms
- A discrepancy principle for Poisson data
- Discrepancy principle for statistical inverse problems with application to conjugate gradient iteration
- Convergence rates in expectation for Tikhonov-type regularization of inverse problems with Poisson data
- Regularization parameter selection methods for ill-posed Poisson maximum likelihood estimation
- Efficient gradient projection methods for edge-preserving removal of Poisson noise
- Poisson intensity estimation for tomographic data using a wavelet shrinkage approach
- Optimal Adaptation for Early Stopping in Statistical Inverse Problems
- Statistical Inverse Estimation in Hilbert Scales
- A modified discrepancy principle to attain optimal convergence rates under unknown noise
- Optimal Convergence of the Discrepancy Principle for Polynomially and Exponentially Ill-Posed Operators under White Noise
- Convergence Rates of General Regularization Methods for Statistical Inverse Problems and Applications
- Lectures on the Poisson Process
- Unfolding intensity function of a Poisson process in models with approximately specified folding operator.
This page was built for publication: Weighted discrepancy principle and optimal adaptivity in Poisson inverse problems
