Zobrazeno 1 - 10
of 104
pro vyhledávání: '"Hassanzadeh, Amin"'
Autor:
Tang, Minxue, Zhang, Jianyi, Ma, Mingyuan, DiValentin, Louis, Ding, Aolin, Hassanzadeh, Amin, Li, Hai, Chen, Yiran
Federated adversarial training can effectively complement adversarial robustness into the privacy-preserving federated learning systems. However, the high demand for memory capacity and computing power makes large-scale federated adversarial training
Externí odkaz:
http://arxiv.org/abs/2209.03839
A machine learning approach feature to forecast the future performance of the universities in Canada
Publikováno v:
Machine Learning with Applications, Vol 16, Iss , Pp 100548- (2024)
University ranking is a technique of measuring the performance of Higher Education Institutions (HEIs) by evaluating them on various criteria like student satisfaction, expenditure, research and teaching quality, citation count, grants, and enrolment
Externí odkaz:
https://doaj.org/article/32ebed613d4348aabcdd5fab70bc7e86
Publikováno v:
Administrative Sciences, Vol 14, Iss 9, p 206 (2024)
Purchasing and procurement managers should make informed decisions in selecting materials at the right time, in sufficient quantities, and at affordable prices. Supplier selection and order allocation (SSOA) is a vital aspect of purchasing and procur
Externí odkaz:
https://doaj.org/article/c680368cf7e64c9ea6b931d059be42de
Federated learning (FL) is a popular distributed learning framework that trains a global model through iterative communications between a central server and edge devices. Recent works have demonstrated that FL is vulnerable to model poisoning attacks
Externí odkaz:
http://arxiv.org/abs/2110.13864
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence, Fall Symposium Series (AAAI-FSS); 2019
As machine learning becomes a more mainstream technology, the objective for governments and public sectors is to harness the power of machine learning to advance their mission by revolutionizing public services. Motivational government use cases requ
Externí odkaz:
http://arxiv.org/abs/2010.05809
Autor:
Hassanzadeh, Amin, Rasekh, Amin, Galelli, Stefano, Aghashahi, Mohsen, Taormina, Riccardo, Ostfeld, Avi, Banks, Katherine
Publikováno v:
ASCE Journal of Environmental Engineering 2020
This study presents a critical review of disclosed, documented, and malicious cybersecurity incidents in the water sector to inform safeguarding efforts against cybersecurity threats. The review is presented within a technical context of industrial c
Externí odkaz:
http://arxiv.org/abs/2001.11144
Publikováno v:
Logistics, Vol 8, Iss 2, p 54 (2024)
Background: Sustainable closed-loop supply chains have emerged as viable answers to supply chain problems. They can handle environmental damages (e.g., waste) and related social impacts. Closed-loop supply chains (CLSCs) are forward and reverse suppl
Externí odkaz:
https://doaj.org/article/98f4cb1c6a6b4aa0b4cb24bd1d22dca9
Publikováno v:
Logistics, Vol 8, Iss 2, p 35 (2024)
Background: This literature review delves into the concept of ‘Third-party Reverse Logistics selection’, focusing on its process and functionality using deterministic and uncertain decision-making models. In an increasingly globalized world, Reve
Externí odkaz:
https://doaj.org/article/505c0156cc6c46058173fe5b605c1535
Publikováno v:
International Journal of Information Management Data Insights, Vol 2, Iss 1, Pp 100058- (2022)
There has been a growing interest in the field of neural networks for prediction in recent years. In this research, a public dataset including the sales history of a retail store is investigated to forecast the sales of furniture. To this aim, severa
Externí odkaz:
https://doaj.org/article/71d7eb0047414197aba01673a1eb834e
Autor:
Samiul Islam, Saman Hassanzadeh Amin
Publikováno v:
Journal of Big Data, Vol 7, Iss 1, Pp 1-22 (2020)
Abstract Prediction using machine learning algorithms is not well adapted in many parts of the business decision processes due to the lack of clarity and flexibility. The erroneous data as inputs in the prediction process may produce inaccurate predi
Externí odkaz:
https://doaj.org/article/cbec54b0a76c4072a29041ecc91b48b8