3 papers
cs.NE2024
Improved Differential Evolution based Feature Selection through Quantum, Chaos, and Lasso
Yelleti Vivek, Sri Krishna Vadlamani, Vadlamani Ravi +1
Modern deep learning continues to achieve outstanding performance on an astounding variety of high-dimensional tasks. In practice, this is obtained by fitting deep neural models to…
cs.NE2024
Quantum-Inspired Evolutionary Algorithms for Feature Subset Selection: A Comprehensive Survey
Yelleti Vivek, Vadlamani Ravi, P. Radha Krishna
The clever hybridization of quantum computing concepts and evolutionary algorithms (EAs) resulted in a new field called quantum-inspired evolutionary algorithms (QIEAs). Unlike tra…
cs.DC2024
Scalable mRMR feature selection to handle high dimensional datasets: Vertical partitioning based Iterative MapReduce framework
Yelleti Vivek, P. S. V. S. Sai Prasad
While building machine learning models, Feature selection (FS) stands out as an essential preprocessing step used to handle the uncertainty and vagueness in the data. Recently, the…