activity
20202022
most citedConditional Variational Autoencoder with Balanced Pre-training for Generative Adversarial Networks

1 citations · 2 across the 4 of their papers we have counts for

collaborators

9 papers

cs.AI20221 cited

Privacy-Preserving Personalized Fitness Recommender System (P3FitRec): A Multi-level Deep Learning Approach

Xiao Liu, Bonan Gao, Basem Suleiman +4

Recommender systems have been successfully used in many domains with the help of machine learning algorithms. However, such applications tend to use multi-dimensional user data, wh…

cs.CV20221 cited

Conditional Variational Autoencoder with Balanced Pre-training for Generative Adversarial Networks

Yuchong Yao, Xiaohui Wangr, Yuanbang Ma +5

Class imbalance occurs in many real-world applications, including image classification, where the number of images in each class differs significantly. With imbalanced data, the ge…

cs.LG2021

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…

cs.LG2021

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…

cs.RO2020

Control Design of Autonomous Drone Using Deep Learning Based Image Understanding Techniques

Seid Miad Zandavi, Vera Chung, Ali Anaissi

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. A new Prop…

cs.NE2020

Multi-User Remote lab: Timetable Scheduling Using Simplex Nondominated Sorting Genetic Algorithm

Seid Miad Zandavi, Vera Chung, Ali Anaissi

The scheduling of multi-user remote laboratories is modeled as a multimodal function for the proposed optimization algorithm. The hybrid optimization algorithm, hybridization of th…