activity
20192021
collaborators

5 papers

cs.LG2021

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…

math.FA2020

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…

cs.IT2019

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…

math.FA2019

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…

math.ST2019

Nonlinear generalization of the monotone single index model

Zeljko Kereta, Timo Klock, Valeriya Naumova

Single index model is a powerful yet simple model, widely used in statistics, machine learning, and other scientific fields. It models the regression function as , where…