Search Results for author:
Found 13 papers, 1 papers with code
Optimisation of federated learning settings under statistical heterogeneity variations
On the basis of these, we present recommended guidelines for FL parameters and aggregators to optimise model performance under different levels of IID and with different datasets
Integration of Self-Supervised BYOL in Semi-Supervised Medical Image Recognition
Image recognition techniques heavily rely on abundant labeled data, particularly in medical contexts.
Damage GAN: A Generative Model for Imbalanced Data
Comparative evaluations against baseline models including the deep convolutional GAN (DCGAN) and ContraD GAN demonstrate the evident superiority of our proposed model, Damage GAN, in terms of generated image distribution, model stability, and image quality when applied to imbalanced datasets.
ResNLS: An Improved Model for Stock Price Forecasting
Stock prices forecasting has always been a challenging task.
Privacy-Preserving Personalized Fitness Recommender System (P3FitRec): A Multi-level Deep Learning Approach
Recommender systems have been successfully used in many domains with the help of machine learning algorithms.
Conditional Variational Autoencoder with Balanced Pre-training for Generative Adversarial Networks
The two recent methods, Balancing GAN (BAGAN) and improved BAGAN (BAGAN-GP), are proposed as an augmentation tool to handle this problem and restore the balance to the data.
A Fast Parallel Tensor Decomposition with Optimal Stochastic Gradient Descent: an Application in Structural Damage Identification
Our approach is based on stochastic gradient descent (SGD) algorithm which allows us to parallelize the learning process and it is very useful in online setting since it updates $\mathcal{X}^{t+1}$ in one single step.
A Personalized Federated Learning Algorithm: an Application in Anomaly Detection
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 central machine learning models.
Control Design of Autonomous Drone Using Deep Learning Based Image Understanding Techniques
This paper presents a new framework to use images as the inputs for the controller to have autonomous flight, considering the noisy indoor environment and uncertainties.
Multi-User Remote lab: Timetable Scheduling Using Simplex Nondominated Sorting Genetic Algorithm
The hybrid optimization algorithm, hybridization of the Nelder-Mead Simplex algorithm and Non-dominated Sorting Genetic Algorithm (NSGA), is proposed to optimize the timetable problem for the remote laboratories to coordinate shared access.
NeCPD: An Online Tensor Decomposition with Optimal Stochastic Gradient Descent
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 \times I_N} $.
Multi-Objective Variational Autoencoder: an Application for Smart Infrastructure Maintenance
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 the hidden correlations between variables in multi-way data.
Online Tensor-Based Learning for Multi-Way Data
The online analysis of multi-way data stored in a tensor $\mathcal{X} \in \mathbb{R} ^{I_1 \times \dots \times I_N} $ has become an essential tool for capturing the underlying structures and extracting the sensitive features which can be used to learn a predictive model.
