Zobrazeno 1 - 10
of 385
pro vyhledávání: '"Rabiee, Hamid"'
Users increasing activity across various social networks made it the most widely used platform for exchanging and propagating information among individuals. To spread information within a network, a user initially shared information on a social netwo
Externí odkaz:
http://arxiv.org/abs/2410.01320
Grapheme-to-phoneme (G2P) conversion is critical in speech processing, particularly for applications like speech synthesis. G2P systems must possess linguistic understanding and contextual awareness of languages with polyphone words and context-depen
Externí odkaz:
http://arxiv.org/abs/2409.08554
In this study, we introduce ManaTTS, the most extensive publicly accessible single-speaker Persian corpus, and a comprehensive framework for collecting transcribed speech datasets for the Persian language. ManaTTS, released under the open CC-0 licens
Externí odkaz:
http://arxiv.org/abs/2409.07259
Decentralized optimization strategies are helpful for various applications, from networked estimation to distributed machine learning. This paper studies finite-sum minimization problems described over a network of nodes and proposes a computationall
Externí odkaz:
http://arxiv.org/abs/2408.02269
Decentralized algorithms have gained substantial interest owing to advancements in cloud computing, Internet of Things (IoT), intelligent transportation networks, and parallel processing over sensor networks. The convergence of such algorithms is dir
Externí odkaz:
http://arxiv.org/abs/2407.01460
Soft prompt tuning techniques have recently gained traction as an effective strategy for the parameter-efficient tuning of pretrained language models, particularly minimizing the required adjustment of model parameters. Despite their growing use, ach
Externí odkaz:
http://arxiv.org/abs/2406.05279
Autor:
Doostmohammadian, Mohammadreza, Qureshi, Muhammad I., Khalesi, Mohammad Hossein, Rabiee, Hamid R., Khan, Usman A.
Decentralized strategies are of interest for learning from large-scale data over networks. This paper studies learning over a network of geographically distributed nodes/agents subject to quantization. Each node possesses a private local cost functio
Externí odkaz:
http://arxiv.org/abs/2406.00621
Meta-learning involves multiple learners, each dedicated to specific tasks, collaborating in a data-constrained setting. In current meta-learning methods, task learners locally learn models from sensitive data, termed support sets. These task learner
Externí odkaz:
http://arxiv.org/abs/2406.00249
Motivation: Drug repurposing is a viable solution for reducing the time and cost associated with drug development. However, thus far, the proposed drug repurposing approaches still need to meet expectations. Therefore, it is crucial to offer a system
Externí odkaz:
http://arxiv.org/abs/2405.08031
The protein-ligand binding affinity (PLA) prediction goal is to predict whether or not the ligand could bind to a protein sequence. Recently, in PLA prediction, deep learning has received much attention. Two steps are involved in deep learning-based
Externí odkaz:
http://arxiv.org/abs/2405.07452