In this paper we provide a novel analytical perspective on the theoretic...
Artificial neural networks are functions depending on a finite number of...
Autoencoding is a popular method in representation learning. Conventiona...
In this paper we study anisotropic consensus-based optimization (CBO), a...
In this work, we consider the optimization formulation for symmetric ten...
In this paper we study consensus-based optimization (CBO), which is a
mu...
In this paper we approach the problem of unique and stable identifiabili...
We study the approximation of two-layer compositions f(x) = g(ϕ(x)) via
...
The multi-index model is a simple yet powerful high-dimensional regressi...
We study the accuracy of estimating the covariance and the precision mat...
We address the structure identification and the uniform approximation of...
Single index model is a powerful yet simple model, widely used in statis...
For many algorithms, parameter tuning remains a challenging and critical...