Zobrazeno 1 - 10
of 5 507
pro vyhledávání: '"A Karapetyan"'
Large language models exhibit a remarkable capacity for in-context learning, where they learn to solve tasks given a few examples. Recent work has shown that transformers can be trained to perform simple regression tasks in-context. This work explore
Externí odkaz:
http://arxiv.org/abs/2410.03140
Many practical applications of optimal control are subject to real-time computational constraints. When applying model predictive control (MPC) in these settings, respecting timing constraints is achieved by limiting the number of iterations of the o
Externí odkaz:
http://arxiv.org/abs/2409.11351
A run of the deferred acceptance (DA) algorithm may contain proposals that are sure to be rejected. We introduce the accelerated deferred acceptance algorithm that proceeds in a similar manner to DA but with sure-to-be rejected proposals ruled out. A
Externí odkaz:
http://arxiv.org/abs/2409.06865
In this paper, we consider the problem of predicting unknown targets from data. We propose Online Residual Learning (ORL), a method that combines online adaptation with offline-trained predictions. At a lower level, we employ multiple offline predict
Externí odkaz:
http://arxiv.org/abs/2409.04069
This study investigates the modulation of particle fluxes at the Earths surface influenced by the intensity and orientation of the Interplanetary magnetic field (IMF) carried by the Coronal Mass Ejecta (ICME). We examine how IMF and its Bz component,
Externí odkaz:
http://arxiv.org/abs/2406.16159
Autor:
Chilingarian, A., Sargsyan, B., Karapetyan, T., Aslanyan, D., Chilingaryan, S., Kozliner, L., Khanikyanc, Y.
In 2023, a series of intense Thunderstorm Ground Enhancements (TGEs) were recorded on Mount Aragats in Armenia, with five events exceeding the fair-weather cosmic ray flux by more than 100 percent. This study comprehensively analyzes these TGEs, inve
Externí odkaz:
http://arxiv.org/abs/2406.16160
In light of growing threats posed by climate change in general and sea level rise (SLR) in particular, the necessity for computationally efficient means to estimate and analyze potential coastal flood hazards has become increasingly pressing. Data-dr
Externí odkaz:
http://arxiv.org/abs/2406.15451
Continuous-time adaptive controllers for systems with a matched uncertainty often comprise an online parameter estimator and a corresponding parameterized controller to cancel the uncertainty. However, such methods are often impossible to implement d
Externí odkaz:
http://arxiv.org/abs/2404.02023
Role mining is a technique used to derive a role-based authorization policy from an existing policy. Given a set of users $U$, a set of permissions $P$ and a user-permission authorization relation $\mahtit{UPA}\subseteq U\times P$, a role mining algo
Externí odkaz:
http://arxiv.org/abs/2403.16757
In this paper, we study the problem of online tracking in linear control systems, where the objective is to follow a moving target. Unlike classical tracking control, the target is unknown, non-stationary, and its state is revealed sequentially, thus
Externí odkaz:
http://arxiv.org/abs/2402.10036