Measuring and Triggering Toxic Behavior in Machine Learning Models
Measuring and Triggering Toxic Behavior in Open-Domain Chatbots
Measuring and Triggering Toxic Behavior in Open-Domain Chatbots
Developing a new model auditing technique that helps users audit machine learning models to determine if their data was used to train these models.
Presenting latent diffusion models, to improve efficiency of de-noising diffusion models without degrading their quality.
Applying static analysis to machine learning code that uses Tensorflow. Paper entitled: Ariadne: Analysis for Machine Learning Programs
Online software to extract and check website information in Python
Design and implementation of an online forecasting software with statistical and machine learning algorithms for stock market data in Python
Put Glasses or Sunglasses on a Person Face in Python
An Automatic Clothing Recognition and Product Suggestions for website or clothing shopping is proposed.
Design and implementation of three new feature selection algorithms for high-dimensional data and the Implementation of tens Hybrid, Wrapper, and filter Feature Selection Algorithms
Published in 3rd national conference on Computer, Information Technology and Artificial Intelligence, 2020
In this paper, fingerprint gender recognition using a combination of three feature vectors was used to extract features to classify the gender of persons.
Recommended citation: K.Shirini, N.R.Zamir M.A.Ganjei, MR.Feizi-Derakhshi(2020). "Improving Gender Recognition Using Fingerprint with SVM, KNN, and Decision Tree." 3rd national conference on Computer, Information Technology and Artificial Intelligence. https://en.civilica.com/doc/1015568/
Published in Akhtar Publication, 2020
This book focuses more on feature selection in supervised learning systems and the final chapters on feature extraction and unsupervised learning.
Recommended citation: M.A.Ganjei, K.Shirini, (2020). "Feature Selection and Dimension Reduction in Machine Learning." Akhtar Publication. https://mohammadahmadig.github.io/publication/2020-09-02-book-1
Published in IEEE 9th International Conference on Computer and Knowledge Engineering (ICCKE), 2020
In this paper, we proposed a new hybrid feature selection method
Recommended citation: M. A. Ganjei and R. Boostani, "A Fast Hybrid Feature Selection Method," 2019 9th International Conference on Computer and Knowledge Engineering (ICCKE), 2019, pp. 6-11, doi: 10.1109/ICCKE48569.2019.8964884. https://ieeexplore.ieee.org/document/8964884
Published in Engineering Applications of Artificial Intelligence, 2022
A new hybrid feature selection framework named the HyCluster is proposed.
Recommended citation: M.A.Ganjei, R.Boostani, (2022). "A Hybrid Feature Selection Scheme for High-Dimensional Data." Engineering Applications of Artificial Intelligence. Volume 113,2022, 104894, https://doi.org/10.1016/j.engappai.2022.104894 https://doi.org/10.1016/j.engappai.2022.104894
Course, Shiraz University, Computer Sciences, Engineering & IT Department, 2018
Courses:
Undergraduate course, Yasouj University, Computer Science & Electrical Engineering Department, 2021
Course: The Design and Analysis of Algorithms at Yasouj University