Zobrazeno 1 - 10
of 4 323
pro vyhledávání: '"Vaca, P."'
Federated Learning (FL) has emerged as a solution for distributed model training across decentralized, privacy-preserving devices, but the different energy capacities of participating devices (system heterogeneity) constrain real-world implementation
Externí odkaz:
http://arxiv.org/abs/2412.02289
Beyond conventional productivity metrics, human interaction and collaboration dynamics merit careful consideration in our increasingly digital workspace. This research proposes a conjectural neuro-adaptive room that enhances group interactions by adj
Externí odkaz:
http://arxiv.org/abs/2410.21571
Autor:
Garrido-Merchán, Eduardo C., Coronado-Vaca, Maria, López-López, Álvaro, de Ibarreta, Carlos Martinez
Traditional economic models often rely on fixed assumptions about market dynamics, limiting their ability to capture the complexities and stochastic nature of real-world scenarios. However, reality is more complex and includes noise, making tradition
Externí odkaz:
http://arxiv.org/abs/2410.20550
Autor:
Kasuluru, Vaishnavi, Blanco, Luis, Vazquez, Miguel Angel, Vaca-Rubio, Cristian J., Zeydan, Engin
This paper deals with the problem of energy consumption minimization in Open RAN cell-free (CF) massive Multiple-Input Multiple-Output (mMIMO) systems under minimum per-user signal-to-noise-plus-interference ratio (SINR) constraints. Considering that
Externí odkaz:
http://arxiv.org/abs/2409.04135
Publikováno v:
A&A 690, A199 (2024)
This work aims to analyze some of the polluters proposed in the self-enrichment scenarios put forward to explain the multiple populations in globular clusters (GCs), extending previous studies. Three scenarios with different polluter stars were teste
Externí odkaz:
http://arxiv.org/abs/2408.09001
Autor:
Zeydan, Engin, Vaca-Rubio, Cristian J., Blanco, Luis, Pereira, Roberto, Caus, Marius, Aydeger, Abdullah
In this paper, we present an innovative federated learning (FL) approach that utilizes Kolmogorov-Arnold Networks (KANs) for classification tasks. By utilizing the adaptive activation capabilities of KANs in a federated framework, we aim to improve c
Externí odkaz:
http://arxiv.org/abs/2407.20100
Financial portfolio management investment policies computed quantitatively by modern portfolio theory techniques like the Markowitz model rely on a set on assumptions that are not supported by data in high volatility markets. Hence, quantitative rese
Externí odkaz:
http://arxiv.org/abs/2407.14486
The transition to sustainable Open Radio Access Network (O-RAN) architectures brings new challenges for resource management, especially in predicting the utilization of Physical Resource Block (PRB)s. In this paper, we propose a novel approach to cha
Externí odkaz:
http://arxiv.org/abs/2407.14400
This paper introduces a novel application of Kolmogorov-Arnold Networks (KANs) to time series forecasting, leveraging their adaptive activation functions for enhanced predictive modeling. Inspired by the Kolmogorov-Arnold representation theorem, KANs
Externí odkaz:
http://arxiv.org/abs/2405.08790
Autor:
Caitlin E. Caspi, Maria Gombi-Vaca, Curtis Antrum, Salma Gudaf, Molly De Marco, Emily Welle, Brett Sheppard, Kristi Fordyce, Rebekah Pratt
Publikováno v:
BMC Public Health, Vol 24, Iss 1, Pp 1-10 (2024)
Abstract Background Economic stability is a core social determinant of health and a necessary condition for maintaining food security, housing stability, and both physical and mental health. Using a qualitative approach, we identified barriers, facil
Externí odkaz:
https://doaj.org/article/e84c8ad491f04151827bc3673e066bd7
