Zobrazeno 1 - 10
of 23 232
pro vyhledávání: '"Driss A."'
Graph Mamba, a powerful graph embedding technique, has emerged as a cornerstone in various domains, including bioinformatics, social networks, and recommendation systems. This survey represents the first comprehensive study devoted to Graph Mamba, to
Externí odkaz:
http://arxiv.org/abs/2412.18322
With the rapid rise of the Internet of Things (IoT), ensuring the security of IoT devices has become essential. One of the primary challenges in this field is that new types of attacks often have significantly fewer samples than more common attacks,
Externí odkaz:
http://arxiv.org/abs/2412.13240
Over the past 7 years, attention has become one of the most important primitives in deep learning. The primary approach to optimize attention is FlashAttention, which fuses the operation together, drastically improving both the runtime and the memory
Externí odkaz:
http://arxiv.org/abs/2412.05496
The abundance of complex and interconnected healthcare data offers numerous opportunities to improve prediction, diagnosis, and treatment. Graph-structured data, which includes entities and their relationships, is well-suited for capturing complex co
Externí odkaz:
http://arxiv.org/abs/2412.05312
Autor:
Berriche, Lamia, Driss, Maha, Almuntashri, Areej Ahmed, Lghabi, Asma Mufreh, Almudhi, Heba Saleh, Almansour, Munerah Abdul-Aziz
This paper introduces a new application named ArPA for Arabic kids who have trouble with pronunciation. Our application comprises two key components: the diagnostic module and the therapeutic module. The diagnostic process involves capturing the chil
Externí odkaz:
http://arxiv.org/abs/2411.13592
Autor:
Espinos, Driss Oumbarek, Zhidkov, Alexei, Rondepierre, Alexandre, Tawada, Masafumi, Masuzawa, Mika
Particle in cell simulations are widely used in most fields of physics to investigate known and new phenomena which cannot be directly observed or measured yet. However, the computational and time resources needed for PICs make them impractical when
Externí odkaz:
http://arxiv.org/abs/2411.04703
Autor:
Lee, Yejin, Sun, Anna, Hosmer, Basil, Acun, Bilge, Balioglu, Can, Wang, Changhan, Hernandez, Charles David, Puhrsch, Christian, Haziza, Daniel, Guessous, Driss, Massa, Francisco, Kahn, Jacob, Wan, Jeffrey, Reizenstein, Jeremy, Zhai, Jiaqi, Isaacson, Joe, Schlosser, Joel, Pino, Juan, Sadagopan, Kaushik Ram, Shamis, Leonid, Ma, Linjian, Hwang, Min-Jae, Chen, Mingda, Elhoushi, Mostafa, Rodriguez, Pedro, Pasunuru, Ram, Yih, Scott, Popuri, Sravya, Liu, Xing, Wu, Carole-Jean
Generative artificial intelligence (AI) technology is revolutionizing the computing industry. Not only its applications have broadened to various sectors but also poses new system design and optimization opportunities. The technology is capable of un
Externí odkaz:
http://arxiv.org/abs/2410.00215
Autor:
Bennis, Driss, Bouziri, Ayoub
Let R be a commutative ring, and let S be a multiplicative subset of R. In this paper, we introduce and investigate the notion of S-FP-injective modules. Among other results, we show that, under certain conditions, a ring R is S-Noetherian if and onl
Externí odkaz:
http://arxiv.org/abs/2410.00167
Federated Learning (FL) has gained attention across various industries for its capability to train machine learning models without centralizing sensitive data. While this approach offers significant benefits such as privacy preservation and decreased
Externí odkaz:
http://arxiv.org/abs/2409.11442
In recent years, research on out-of-distribution (OoD) detection for semantic segmentation has mainly focused on road scenes -- a domain with a constrained amount of semantic diversity. In this work, we challenge this constraint and extend the domain
Externí odkaz:
http://arxiv.org/abs/2407.15739