Zobrazeno 1 - 10
of 40 267
pro vyhledávání: '"A. Ghani"'
Autor:
Jagatheesaperumal, Senthil Kumar, Rahouti, Mohamed, Alfatemi, Ali, Ghani, Nasir, Quy, Vu Khanh, Chehri, Abdellah
Publikováno v:
IEEE Internet of Things Magazine, Year: 2024, Volume: 7, Issue: 5
Federated Learning (FL) represents a paradigm shift in machine learning, allowing collaborative model training while keeping data localized. This approach is particularly pertinent in the Industrial Internet of Things (IIoT) context, where data priva
Externí odkaz:
http://arxiv.org/abs/2409.02127
Models for categorical sequences typically assume exchangeable or first-order dependent sequence elements. These are common assumptions, for example, in models of computer malware traces and protein sequences. Although such simplifying assumptions le
Externí odkaz:
http://arxiv.org/abs/2407.19236
Autor:
Sarkar, Soumya, Han, Zirun, Ghani, Maheera Abdul, Strkalj, Nives, Kim, Jung Ho, Wang, Yan, Jariwala, Deep, Chhowalla, Manish
Some van der Waals (vdW) materials exhibit ferroelectricity, making them promising for novel non-volatile memories (NVMs) such as ferroelectric diodes (FeDs). CuInP2S6 (CIPS) is a well-known vdW ferroelectric that has been integrated with graphene fo
Externí odkaz:
http://arxiv.org/abs/2407.09175
Artificial intelligence (AI) systems of autonomous systems such as drones, robots and self-driving cars may consume up to 50% of total power available onboard, thereby limiting the vehicle's range of functions and considerably reducing the distance t
Externí odkaz:
http://arxiv.org/abs/2407.04717
Autor:
Martinez, Fernando, Mapkar, Mariyam, Alfatemi, Ali, Rahouti, Mohamed, Xin, Yufeng, Xiong, Kaiqi, Ghani, Nasir
Distributed Denial of Service (DDoS) attacks pose an increasingly substantial cybersecurity threat to organizations across the globe. In this paper, we introduce a new deep learning-based technique for detecting DDoS attacks, a paramount cybersecurit
Externí odkaz:
http://arxiv.org/abs/2406.02632
Autor:
Jesus, Sérgio, Saleiro, Pedro, Silva, Inês Oliveira e, Jorge, Beatriz M., Ribeiro, Rita P., Gama, João, Bizarro, Pedro, Ghani, Rayid
Aequitas Flow is an open-source framework for end-to-end Fair Machine Learning (ML) experimentation in Python. This package fills the existing integration gaps in other Fair ML packages of complete and accessible experimentation. It provides a pipeli
Externí odkaz:
http://arxiv.org/abs/2405.05809
We propose a categorical semantics for machine learning algorithms in terms of lenses, parametric maps, and reverse derivative categories. This foundation provides a powerful explanatory and unifying framework: it encompasses a variety of gradient de
Externí odkaz:
http://arxiv.org/abs/2404.00408
Detecting the presence of animal vocalisations in nature is essential to study animal populations and their behaviors. A recent development in the field is the introduction of the task known as few-shot bioacoustic sound event detection, which aims t
Externí odkaz:
http://arxiv.org/abs/2403.18638
This paper presents a self-supervised learning method to safely learn a motion planner for ground robots to navigate environments with dense and dynamic obstacles. When facing highly-cluttered, fast-moving, hard-to-predict obstacles, classical motion
Externí odkaz:
http://arxiv.org/abs/2403.17231
Autor:
Vajiac, Catalina, Frey, Arun, Baumann, Joachim, Smith, Abigail, Amarasinghe, Kasun, Lai, Alice, Rodolfa, Kit, Ghani, Rayid
Rental assistance programs provide individuals with financial assistance to prevent housing instabilities caused by evictions and avert homelessness. Since these programs operate under resource constraints, they must decide who to prioritize. Typical
Externí odkaz:
http://arxiv.org/abs/2403.12599