13 citations · 25 across the 28 of their papers we have counts for
12 papers · 1 filter
Tensor-based Fusion of Multi-modal Data for Predicting Cancer Risk Levels
Ali Anaissi, Yuanzhe Jia, Qishun Peng +3
Cancer diagnosis and treatment increasingly rely on multi-modal diagnostic technologies that generate high-dimensional datasets. Although these datasets are rich in pathological in…
Rethinking the Information Bottleneck: Structured Decomposition under Label-Induced Partitions
Jingyao Zhang, Yuxuan Li, Lu Han +2
Standard information bottleneck (IB) regularization constrains representations via a single scalar I(Z;X), implicitlytreating all information as homogeneous. However, a single glob…
A Hybrid Computational Intelligence Framework for scRNA-seq Imputation: Integrating scRecover and Random Forests
Ali Anaissi, Deshao Liu, Yuanzhe Jia +3
Single-cell RNA sequencing (scRNA-seq) enables transcriptomic profiling at cellular resolution but suffers from pervasive dropout events that obscure biological signals. We present…
FedSAF: A Federated Learning Framework for Enhanced Gastric Cancer Detection and Privacy Preservation
Yuxin Miao, Xinyuan Yang, Hongda Fan +6
Gastric cancer is one of the most commonly diagnosed cancers and has a high mortality rate. Due to limited medical resources, developing machine learning models for gastric cancer…
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…
Damage GAN: A Generative Model for Imbalanced Data
Ali Anaissi, Yuanzhe Jia, Ali Braytee +2
This study delves into the application of Generative Adversarial Networks (GANs) within the context of imbalanced datasets. Our primary aim is to enhance the performance and stabil…
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…