Zobrazeno 1 - 10
of 76
pro vyhledávání: '"Abdelmoniem, Ahmed M."'
Autor:
Li, Qilei, Abdelmoniem, Ahmed M.
Federated Learning (FL) is a distributed machine learning diagram that enables multiple clients to collaboratively train a global model without sharing their private local data. However, FL systems are vulnerable to attacks that are happening in mali
Externí odkaz:
http://arxiv.org/abs/2408.02813
The training of large models, involving fine-tuning, faces the scarcity of high-quality data. Compared to the solutions based on centralized data centers, updating large models in the Internet of Things (IoT) faces challenges in coordinating knowledg
Externí odkaz:
http://arxiv.org/abs/2407.05268
Autor:
Agarwal, Vibhor, Raman, Aravindh, Sastry, Nishanth, Abdelmoniem, Ahmed M., Tyson, Gareth, Castro, Ignacio
The recent development of decentralised and interoperable social networks (such as the "fediverse") creates new challenges for content moderators. This is because millions of posts generated on one server can easily "spread" to another, even if the r
Externí odkaz:
http://arxiv.org/abs/2404.03048
In Federated Learning (FL), forgetting, or the loss of knowledge across rounds, hampers algorithm convergence, particularly in the presence of severe data heterogeneity among clients. This study explores the nuances of this issue, emphasizing the cri
Externí odkaz:
http://arxiv.org/abs/2402.05558
Autor:
Abdelmoniem, Ahmed M., Bensaou, Brahim
The peculiar congestion patterns in data centers are caused by the bursty and composite nature of traffic, the small bandwidth-delay product, and the tiny switch buffers. It is not practical to modify TCP to adapt to data centers, especially in publi
Externí odkaz:
http://arxiv.org/abs/2401.04850
In today's world, the rapid expansion of IoT networks and the proliferation of smart devices in our daily lives, have resulted in the generation of substantial amounts of heterogeneous data. These data forms a stream which requires special handling.
Externí odkaz:
http://arxiv.org/abs/2312.15375
Publikováno v:
Elsevier Journal of Economy and Technology 2024
Companies across the globe are keen on targeting potential high-value customers in an attempt to expand revenue and this could be achieved only by understanding the customers more. Customer Lifetime Value (CLV) is the total monetary value of transact
Externí odkaz:
http://arxiv.org/abs/2308.08502
Publikováno v:
Published In book: Applications of AI for Interdisciplinary Research, Edition: First, Chapter: 8, Publisher: CRC Press, July 2024
One of the most enticing research areas is the stock market, and projecting stock prices may help investors profit by making the best decisions at the correct time. Deep learning strategies have emerged as a critical technique in the field of the fin
Externí odkaz:
http://arxiv.org/abs/2308.04419
Autor:
Bragion, Eric, Akter, Habiba, Kumar, Mohit, Xu, Minxian, Abdelmoniem, Ahmed M., Gill, Sukhpal Singh
Publikováno v:
Published in Internet of Things and Cyber-Physical Systems, Volume 3, 2023, Pages 272-279
Digitalisation, accelerated by the pandemic, has brought the opportunity for companies to expand their businesses beyond their geographic location and has considerably affected networks around the world. Cloud services have a better acceptance nowada
Externí odkaz:
http://arxiv.org/abs/2307.13602
Autor:
Abdelmoniem, Ahmed M.
With mobile, IoT and sensor devices becoming pervasive in our life and recent advances in Edge Computational Intelligence (e.g., Edge AI/ML), it became evident that the traditional methods for training AI/ML models are becoming obsolete, especially w
Externí odkaz:
http://arxiv.org/abs/2306.10848