8 citations · 27 across the 24 of their papers we have counts for
9 papers · 1 filter
New Money: A Systematic Review of Synthetic Data Generation for Finance
James Meldrum, Basem Suleiman, Fethi Rabhi +1
Synthetic data generation has emerged as a promising approach to address the challenges of using sensitive financial data in machine learning applications. By leveraging generative…
Enforcing Consistency and Fairness in Multi-level Hierarchical Classification with a Mask-based Output Layer
Shijing Chen, Shoaib Jameel, Mohamed Reda Bouadjenek +6
Traditional Multi-level Hierarchical Classification (MLHC) classifiers often rely on backbone models with independent output layers. This structure tends to overlook the hierar…
Optimisation of federated learning settings under statistical heterogeneity variations
Basem Suleiman, Muhammad Johan Alibasa, Rizka Widyarini Purwanto +3
Federated Learning (FL) enables local devices to collaboratively learn a shared predictive model by only periodically sharing model parameters with a central aggregator. However, F…
ResNLS: An Improved Model for Stock Price Forecasting
Yuanzhe Jia, Ali Anaissi, Basem Suleiman
Stock prices forecasting has always been a challenging task. Although many research projects try to address the problem, few of them pay attention to the varying degrees of depende…
A Fast Parallel Tensor Decomposition with Optimal Stochastic Gradient Descent: an Application in Structural Damage Identification
Ali Anaissi, Basem Suleiman, Seid Miad Zandavi
Structural Health Monitoring (SHM) provides an economic approach which aims to enhance understanding the behavior of structures by continuously collects data through multiple netwo…
A Personalized Federated Learning Algorithm: an Application in Anomaly Detection
Ali Anaissi, Basem Suleiman
Federated Learning (FL) has recently emerged as a promising method that employs a distributed learning model structure to overcome data privacy and transmission issues paused by ce…
NeCPD: An Online Tensor Decomposition with Optimal Stochastic Gradient Descent
Ali Anaissi, Basem Suleiman, Seid Miad Zandavi
Multi-way data analysis has become an essential tool for capturing underlying structures in higher-order datasets stored in tensor $\mathcal{X} \in \mathbb{R} ^{I_1 \times \dots \t…
Multi-Objective Variational Autoencoder: an Application for Smart Infrastructure Maintenance
Ali Anaissi, Seid Miad Zandavi
Multi-way data analysis has become an essential tool for capturing underlying structures in higher-order data sets where standard two-way analysis techniques often fail to discover…
Online Tensor-Based Learning for Multi-Way Data
Ali Anaissi, Basem Suleiman, Seid Miad Zandavi
The online analysis of multi-way data stored in a tensor has become an essential tool for capturing the underlying stru…