Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Avanesov, Valeriy"'
Autor:
Avanesov, Valeriy
The ever-growing size of the datasets renders well-studied learning techniques, such as Kernel Ridge Regression, inapplicable, posing a serious computational challenge. Divide-and-conquer is a common remedy, suggesting to split the dataset into disjo
Externí odkaz:
http://arxiv.org/abs/2105.11425
Autor:
Avanesov, Valeriy
Wir betrachten die Detektion und Lokalisation von plötzlichen Änderungen in der Kovarianzstruktur hochdimensionaler zufälliger Daten. Diese Arbeit schlägt zwei neuartige Ansätze für dieses Problem vor. Die Vorgehensweise beinhaltet im Wesentlic
Externí odkaz:
http://edoc.hu-berlin.de/18452/19526
Autor:
Avanesov, Valeriy
Gaussian Process Regression and Kernel Ridge Regression are popular nonparametric regression approaches. Unfortunately, they suffer from high computational complexity rendering them inapplicable to the modern massive datasets. To that end a number of
Externí odkaz:
http://arxiv.org/abs/1912.06689
Autor:
Avanesov, Valeriy
In $\mathcal{X}$-armed bandit problem an agent sequentially interacts with environment which yields a reward based on the vector input the agent provides. The agent's goal is to maximise the sum of these rewards across some number of time steps. The
Externí odkaz:
http://arxiv.org/abs/1908.07636
Autor:
Avanesov, Valeriy
This paper considers the prominent problem of change-point detection in regression. The study suggests a novel testing procedure featuring a fully data-driven calibration scheme. The method is essentially a black box, requiring no tuning from the pra
Externí odkaz:
http://arxiv.org/abs/1903.02603
Autor:
Avanesov, Valeriy
We consider detection and localization of an abrupt break in the covariance structure of high-dimensional random data. The paper proposes a novel testing procedure for this problem. Due to its nature, the approach requires a properly chosen critical
Externí odkaz:
http://arxiv.org/abs/1803.00508
Autor:
Buzun, Nazar, Avanesov, Valeriy
In Change point detection task Likelihood Ratio Test (LRT) is sequentially applied in a sliding window procedure. Its high values indicate changes of parametric distribution in the data sequence. Correspondingly LRT values require predefined bound fo
Externí odkaz:
http://arxiv.org/abs/1710.07285
Autor:
Avanesov, Valeriy, Buzun, Nazar
Publikováno v:
Electron. J. Statist. Volume 12, Number 2 (2018), 3254-3294
In this paper we introduce a novel approach for an important problem of break detection. Specifically, we are interested in detection of an abrupt change in the covariance structure of a high-dimensional random process -- a problem, which has applica
Externí odkaz:
http://arxiv.org/abs/1610.03783
Autor:
Avanesov, Valeriy
In X-armed bandit problem an agent sequentially interacts with environment which yields a reward based on the vector input the agent provides. The agent's goal is to maximise the sum of these rewards across some number of time steps. The problem and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d6a6d2a135acc3b3ef056766bca441b2
In this paper we consider the adaptive '1-penalized estimators for the precision matrix in a finite-sample setting. We show consistency results and construct confidence intervals for the elements of the true precision matrix. Additionally, we analyze
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::618d205a8bf6df50bbe3842e95267a1c