research
∙
04/20/2023
Interpolation property of shallow neural networks
We study the geometry of global minima of the loss landscape of overpara...
share
research
∙
09/03/2022
From Monte Carlo to neural networks approximations of boundary value problems
In this paper we study probabilistic and neural network approximations f...
research
∙
04/01/2022
LoCoV: low dimension covariance voting algorithm for portfolio optimization
Minimum-variance portfolio optimizations rely on accurate covariance est...
research
∙
02/28/2022
A Dynamical Estimation and Prediction for Covid19 on Romania using ensemble neural networks
In this paper, we propose an analysis of Covid19 evolution and predictio...
research
∙
01/01/2022
Recover the spectrum of covariance matrix: a non-asymptotic iterative method
It is well known the sample covariance has a consistent bias in the spec...
research
∙
07/27/2020
A regime switching on Covid19 analysis and prediction in Romania
In this paper we propose a regime separation for the analysis of Covid19...
research
∙
06/23/2020
A self-supervised neural-analytic method to predict the evolution of COVID-19 in Romania
Analysing and understanding the transmission and evolution of the COVID-...
research
∙
05/30/2020
An Analytical Formula for Spectrum Reconstruction
We study the spectrum reconstruction technique. As is known to all, eige...
research
∙
06/10/2019
A cost-reducing partial labeling estimator in text classification problem
We propose a new approach to address the text classification problems wh...
research
∙
05/08/2019
Naive Bayes with Correlation Factor for Text Classification Problem
Naive Bayes estimator is widely used in text classification problems. Ho...
research
∙
04/25/2018
