activity
20192022
most citedSearch Algorithms for Automated Hyper-Parameter Tuning

43 citations · 52 across the 10 of their papers we have counts for

collaborators

12 papers

cs.CV2022★ 2 cited

3D-model ShapeNet Core Classification using Meta-Semantic Learning

Farid Ghareh Mohammadi, Cheng Chen, Farzan Shenavarmasouleh +3

Understanding 3D point cloud models for learning purposes has become an imperative challenge for real-world identification such as autonomous driving systems. A wide variety of sol…

cs.NE2022

The application of Evolutionary and Nature Inspired Algorithms in Data Science and Data Analytics

Farid Ghareh Mohammadi, Farzan Shenavarmasouleh, Khaled Rasheed +3

In the past 30 years, scientists have searched nature, including animals and insects, and biology in order to discover, understand, and model solutions for solving large-scale scie…

cs.LG2021

Data Analytics for Smart cities: Challenges and Promises

Farid Ghareh Mohammadi, Farzan Shenavarmasouleh, M. Hadi Amini +1

The explosion of advancements in artificial intelligence, sensor technologies, and wireless communication activates ubiquitous sensing through distributed sensors. These sensors ar…

cs.LG2021

HyP-ABC: A Novel Automated Hyper-Parameter Tuning Algorithm Using Evolutionary Optimization

Leila Zahedi, Farid Ghareh Mohammadi, M. Hadi Amini

Machine learning techniques lend themselves as promising decision-making and analytic tools in a wide range of applications. Different ML algorithms have various hyper-parameters.…

cs.AI2021

Embodied AI-Driven Operation of Smart Cities: A Concise Review

Farzan Shenavarmasouleh, Farid Ghareh Mohammadi, M. Hadi Amini +1

A smart city can be seen as a framework, comprised of Information and Communication Technologies (ICT). An intelligent network of connected devices that collect data with their sen…

cs.LG2021★ 43 cited

Search Algorithms for Automated Hyper-Parameter Tuning

Leila Zahedi, Farid Ghareh Mohammadi, Shabnam Rezapour +2

Machine learning is a powerful method for modeling in different fields such as education. Its capability to accurately predict students' success makes it an ideal tool for decision…

cs.CR2020★ 7 cited

Malware Detection using Artificial Bee Colony Algorithm

Farid Ghareh Mohammadi, Farzan Shenavarmasouleh, M. Hadi Amini +1

Malware detection has become a challenging task due to the increase in the number of malware families. Universal malware detection algorithms that can detect all the malware famili…

eess.IV2020

DRDr II: Detecting the Severity Level of Diabetic Retinopathy Using Mask RCNN and Transfer Learning

Farzan Shenavarmasouleh, Farid Ghareh Mohammadi, M. Hadi Amini +1

DRDr II is a hybrid of machine learning and deep learning worlds. It builds on the successes of its antecedent, namely, DRDr, that was trained to detect, locate, and create segment…

cs.CV2020

On Parameter Tuning in Meta-learning for Computer Vision

Farid Ghareh Mohammadi, M. Hadi Amini, Hamid R. Arabnia

Learning to learn plays a pivotal role in meta-learning (MTL) to obtain an optimal learning model. In this paper, we investigate mage recognition for unseen categories of a given d…

cs.LG2019

An Introduction to Advanced Machine Learning : Meta Learning Algorithms, Applications and Promises

Farid Ghareh Mohammadi, M. Hadi Amini, Hamid R. Arabnia

In [1, 2], we have explored the theoretical aspects of feature extraction optimization processes for solving largescale problems and overcoming machine learning limitations. Majori…

cs.LG2019

Applications of Nature-Inspired Algorithms for Dimension Reduction: Enabling Efficient Data Analytics

Farid Ghareh Mohammadi, M. Hadi Amini, Hamid R. Arabnia

In [1], we have explored the theoretical aspects of feature selection and evolutionary algorithms. In this chapter, we focus on optimization algorithms for enhancing data analytic…

cs.NE2019

Evolutionary Computation, Optimization and Learning Algorithms for Data Science

Farid Ghareh Mohammadi, M. Hadi Amini, Hamid R. Arabnia

A large number of engineering, science and computational problems have yet to be solved in a computationally efficient way. One of the emerging challenges is how evolving technolog…