Zobrazeno 1 - 10
of 4 322
pro vyhledávání: '"Bakhshi P"'
We propose an algorithm of approximating the optimal objective value of a two-stage stochastic program under an assumption of {\it approximate rotational invariance} of the technology matrix, and compare the method with the L-shaped decomposition.
Externí odkaz:
http://arxiv.org/abs/2407.21215
Autor:
Deekshitha, Farshidi, Siamak, Maassen, Jason, Bakhshi, Rena, van Nieuwpoort, Rob, Jansen, Slinger
The growing usage of research software in the research community has highlighted the need to recognize and acknowledge the contributions made not only by researchers but also by Research Software Engineers. However, the existing methods for crediting
Externí odkaz:
http://arxiv.org/abs/2406.02412
Autor:
Deekshitha, Bakhshi, Rena, Maassen, Jason, Ortiz, Carlos Martinez, van Nieuwpoort, Rob, Jansen, Slinger
The organizations and researchers producing research software face a common problem of making their software sustainable beyond funding provided by a single research project. This is addressed by research software engineers through building communiti
Externí odkaz:
http://arxiv.org/abs/2406.01788
Effective data routing is vital in the Internet of Things (IoT) paradigm, especially in underwater mobile sensor networks where inefficiency can lead to significant resource consumption. This article presents an innovative method designed to enhance
Externí odkaz:
http://arxiv.org/abs/2405.11513
We consider the problem of maximizing $\langle c,x \rangle$ subject to the constraints $Ax \leq \mathbf{1}$, where $x\in{\mathbb R}^n$, $A$ is an $m\times n$ matrix with mutually independent centered subgaussian entries of unit variance, and $c$ is a
Externí odkaz:
http://arxiv.org/abs/2401.17530
Autor:
Bakhshi, Sepehr, Can, Fazli
Available works addressing multi-label classification in a data stream environment focus on proposing accurate models; however, these models often exhibit inefficiency and cannot balance effectiveness and efficiency. In this work, we propose a neural
Externí odkaz:
http://arxiv.org/abs/2310.00665
Ensemble methods are commonly used in classification due to their remarkable performance. Achieving high accuracy in a data stream environment is a challenging task considering disruptive changes in the data distribution, also known as concept drift.
Externí odkaz:
http://arxiv.org/abs/2308.10807
Process mining can help acquire insightful knowledge and heighten the system's performance. In this study, we surveyed the trajectories of 1050 sepsis patients in a regional hospital in the Netherlands from the registration to the discharge phase. Ba
Externí odkaz:
http://arxiv.org/abs/2303.14328
Autor:
Kahvazadeh, Sarang, Khalili, Hamzeh, Silab, Rasoul Nikbakht, Bakhshi, Bahador, Mangues-Bafalluy, Josep
5G realizes an impactful convergence, where Network Functions Virtualization (NFV) and cloud-native models become fundamental for profiting from the unprecedented capacity offered at the 5G Radio Access Network (RAN). For providing scalability and au
Externí odkaz:
http://arxiv.org/abs/2211.14078
Autor:
Martinez-Ortiz, Carlos, Bakhshi, Rena, Dzigan, Yifat, Renaud, Nicolas, Diblen, Faruk, Weel, Berend, van Meersbergen, Maarten, Drost, Niels, van der Burg, Sven, Fakhereh, Alidoost
This paper presents the types of teams that are currently in place at the Netherlands eScience Center. We categorize our teams into four different types: Project Teams, Collectives, Agile Teams and Scrum Teams. We provide a brief description of each
Externí odkaz:
http://arxiv.org/abs/2204.08783