686 citations · 1.5k across the 39 of their papers we have counts for
12 papers · 1 filter
A Survey on Recent Random Walk-based Methods for Embedding Knowledge Graphs
Elika Bozorgi, Sakher Khalil Alqaiidi, Afsaneh Shams +2
Machine learning, deep learning, and NLP methods on knowledge graphs are present in different fields and have important roles in various domains from self-driving cars to friend re…
Subgraph2vec: A random walk-based algorithm for embedding knowledge graphs
Elika Bozorgi, Saber Soleimani, Sakher Khalil Alqaiidi +2
Graph is an important data representation which occurs naturally in the real world applications \cite{goyal2018graph}. Therefore, analyzing graphs provides users with better insigh…
Deep Learning in Healthcare: An In-Depth Analysis
Farzan Shenavarmasouleh, Farid Ghareh Mohammadi, Khaled M. Rasheed +1
Deep learning (DL) along with never-ending advancements in computational processing and cloud technologies have bestowed us powerful analyzing tools and techniques in the past deca…
EXPANSE: A Deep Continual / Progressive Learning System for Deep Transfer Learning
Mohammadreza Iman, John A. Miller, Khaled Rasheed +2
Deep transfer learning techniques try to tackle the limitations of deep learning, the dependency on extensive training data and the training costs, by reusing obtained knowledge. H…
Applications of Machine Learning in Healthcare and Internet of Things (IOT): A Comprehensive Review
Farid Ghareh Mohammadi, Farzan Shenavarmasouleh, Hamid R. Arabnia
In recent years, smart healthcare IoT devices have become ubiquitous, but they work in isolated networks due to their policy. Having these devices connected in a network enables us…
A Review of Deep Transfer Learning and Recent Advancements
Mohammadreza Iman, Khaled Rasheed, Hamid R. Arabnia
Deep learning has been the answer to many machine learning problems during the past two decades. However, it comes with two major constraints: dependency on extensive labeled data…