6 citations · 6 across the 2 of their papers we have counts for
8 papers
StreaMRAK a Streaming Multi-Resolution Adaptive Kernel Algorithm
Andreas Oslandsbotn, Zeljko Kereta, Valeriya Naumova +2
Kernel ridge regression (KRR) is a popular scheme for non-linear non-parametric learning. However, existing implementations of KRR require that all the data is stored in the main m…
Quantifying Sources of Uncertainty in Deep Learning-Based Image Reconstruction
Riccardo Barbano, Željko Kereta, Chen Zhang +3
Image reconstruction methods based on deep neural networks have shown outstanding performance, equalling or exceeding the state-of-the-art results of conventional approaches, but o…
Construction and Monte Carlo estimation of wavelet frames generated by a reproducing kernel
Ernesto De Vito, Zeljko Kereta, Valeriya Naumova +2
We introduce a construction of multiscale tight frames on general domains. The frame elements are obtained by spectral filtering of the integral operator associated with a reproduc…
Estimating covariance and precision matrices along subspaces
Zeljko Kereta, Timo Klock
We study the accuracy of estimating the covariance and the precision matrix of a -variate sub-Gaussian distribution along a prescribed subspace or direction using the finite sam…
Computational approaches to non-convex, sparsity-inducing multi-penalty regularization
Zeljko Kereta, Johannes Maly, Valeriya Naumova
In this work we consider numerical efficiency and convergence rates for solvers of non-convex multi-penalty formulations when reconstructing sparse signals from noisy linear measur…
Monte Carlo wavelets: a randomized approach to frame discretization
Zeljko Kereta, Stefano Vigogna, Valeriya Naumova +2
In this paper we propose and study a family of continuous wavelets on general domains, and a corresponding stochastic discretization that we call Monte Carlo wavelets. First, using…