24 citations · 53 across the 11 of their papers we have counts for
11 papers
Minimax-Optimal Early Stopping for Continuous-Time SGD via the Discrepancy Principle
Tim Jahn, Loucas Pillaud-Vivien, Adrien Schertzer
We study early stopping for a continuous-time model of stochastic gradient descent (SGD) in ill-posed linear inverse problems. We consider an a posteriori stopping rule based on th…
On the convergence of an adaptive denoiser driven iterative regularization with early stopping
Harshit Bajpai, Ankik Kumar Giri, Tim Jahn +1
Solving inverse problems requires appropriate regularization techniques to ensure well-posedness and stability. In recent years, denoiser-driven methods have emerged as effective r…
Noise level free regularisation of general linear inverse problems under unconstrained white noise
Tim Jahn
In this note we solve a general statistical inverse problem under absence of knowledge of both the noise level and the noise distribution via application of the (modified) heuristi…
Discretisation-adaptive regularisation of statistical inverse problems
Tim Jahn
We consider linear inverse problems under white noise. These types of problems can be tackled with, e.g., iterative regularisation methods and the main challenge is to determine a…
A Probabilistic Oracle Inequality and Quantification of Uncertainty of a modified Discrepancy Principle for Statistical Inverse Problems
Tim Jahn
In this note we consider spectral cut-off estimators to solve a statistical linear inverse problem under arbitrary white noise. The truncation level is determined with a recently i…
Optimal Convergence of the Discrepancy Principle for polynomially and exponentially ill-posed Operators under White Noise
Tim Jahn
We consider a linear ill-posed equation in the Hilbert space setting under white noise. Known convergence results for the discrepancy principle are either restricted to Hilbert-Sch…