4 citations · 7 across the 37 of their papers we have counts for
9 papers · 1 filter
Detecting Popular Social Events through Limited Observation with Deep Survival Analysis
Maryam Ramezani, Hossein Goli, AmirMohammad Izadi +1
Users increasing activity across various social networks made it the most widely used platform for exchanging and propagating information among individuals. To spread information w…
LLM-Powered Grapheme-to-Phoneme Conversion: Benchmark and Case Study
Mahta Fetrat Qharabagh, Zahra Dehghanian, Hamid R. Rabiee
Grapheme-to-phoneme (G2P) conversion is critical in speech processing, particularly for applications like speech synthesis. G2P systems must possess linguistic understanding and co…
ManaTTS Persian: a recipe for creating TTS datasets for lower resource languages
Mahta Fetrat Qharabagh, Zahra Dehghanian, Hamid R. Rabiee
In this study, we introduce ManaTTS, the most extensive publicly accessible single-speaker Persian corpus, and a comprehensive framework for collecting transcribed speech datasets…
Nonlinear Perturbation-based Non-Convex Optimization over Time-Varying Networks
Mohammadreza Doostmohammadian, Zulfiya R. Gabidullina, Hamid R. Rabiee
Decentralized optimization strategies are helpful for various applications, from networked estimation to distributed machine learning. This paper studies finite-sum minimization pr…
How Clustering Affects the Convergence of Decentralized Optimization over Networks: A Monte-Carlo-based Approach
Mohammadreza Doostmohammadian, Shahaboddin Kharazmi, Hamid R. Rabiee
Decentralized algorithms have gained substantial interest owing to advancements in cloud computing, Internet of Things (IoT), intelligent transportation networks, and parallel proc…
Log-Scale Quantization in Distributed First-Order Methods: Gradient-based Learning from Distributed Data
Mohammadreza Doostmohammadian, Muhammad I. Qureshi, Mohammad Hossein Khalesi +2
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 sub…
Privacy Challenges in Meta-Learning: An Investigation on Model-Agnostic Meta-Learning
Mina Rafiei, Mohammadmahdi Maheri, Hamid R. Rabiee
Meta-learning involves multiple learners, each dedicated to specific tasks, collaborating in a data-constrained setting. In current meta-learning methods, task learners locally lea…
HGTDR: Advancing Drug Repurposing with Heterogeneous Graph Transformers
Ali Gharizadeh, Karim Abbasi, Amin Ghareyazi +2
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…
PLA-SGCN: Protein-Ligand Binding Affinity Prediction by Integrating Similar Pairs and Semi-supervised Graph Convolutional Network
Karim Abbasi, Parvin Razzaghi, Amin Ghareyazi +1
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 r…