We generalize several important results from the perturbation theory of linear operators to
the setting of semisimple orthogonal symmetric Lie algebras. These Lie algebras provide a …

We study kernel least-squares estimation under a norm constraint. This form of
regularisation is known as Ivanov regularisation and it provides better control of the norm of …

Due to its better results over the traditional co-simulation methods, joint simulation of
variables through orthogonal factors has gained popularity. In this approach, practitioners …

The Goldenshluger-Lepski method for constrained least-squares estimators over RKHSs Page 1
Bernoulli 27(4), 2021, 2241–2266 https://doi.org/10.3150/20-BEJ1307 The Goldenshluger–Lepski …

Standard subspaces are a well studied object in algebraic quantum field theory (AQFT).
Given a standard subspace ${\tt V} $ of a Hilbert space $\mathcal {H} $, one is interested in …

This thesis develops a method of reduced control systems and applies it to quantum control
theory. First we address open Markovian quantum systems with fast unitary control, which …

We derive new estimates for the first Betti number of compact Riemannian manifolds. Our
approach relies on the Birman-Schwinger principle and Schatten norm estimates for …

We study kernel least-squares estimators for the regression problem subject to a norm
constraint. We bound the squared L 2 error of our estimators with respect to the covariate …

We derive new estimates for the first Betti number of compact Riemannian manifolds. Our
approach relies on the Birman–Schwinger principle and Schatten norm estimates for …

The quality properties of andesite (Unit Volume Weight, Uniaxial Compression Strength,
Los500, etc.) are required to determine the exploitable blocks and their sequence of …