13 citations · 34 across the 8 of their papers we have counts for
11 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…
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…
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…
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…
Robust Recovery of Low-Rank Matrices with Non-Orthogonal Sparse Decomposition from Incomplete Measurements
Massimo Fornasier, Johannes Maly, Valeriya Naumova
We consider the problem of recovering an unknown effectively -sparse low-rank- matrix with possibly non-orthogonal rank- decomposition from incomplete and inac…
Adaptive multi-penalty regularization based on a generalized Lasso path
Markus Grasmair, Timo Klock, Valeriya Naumova
For many algorithms, parameter tuning remains a challenging and critical task, which becomes tedious and infeasible in a multi-parameter setting. Multi-penalty regularization, succ…
Dictionary Learning from Incomplete Data
Valeriya Naumova, Karin Schnass
This paper extends the recently proposed and theoretically justified iterative thresholding and residual means algorithm ITKrM to learning dicionaries from incomplete/masked tr…
A Machine Learning Approach to Optimal Tikhonov Regularisation I: Affine Manifolds
Ernesto De Vito, Massimo Fornasier, Valeriya Naumova
Despite a variety of available techniques the issue of the proper regularization parameter choice for inverse problems still remains one of the biggest challenges. The main difficu…
Conditions on optimal support recovery in unmixing problems by means of multi-penalty regularization
Markus Grasmair, Valeriya Naumova
Inspired by several real-life applications in audio processing and medical image analysis, where the quantity of interest is generated by several sources to be accurately modeled a…
Minimization of multi-penalty functionals by alternating iterative thresholding and optimal parameter choices
Valeriya Naumova, Steffen Peter
Inspired by several recent developments in regularization theory, optimization, and signal processing, we present and analyze a numerical approach to multi-penalty regularization i…