15 citations · 16 across the 3 of their papers we have counts for
3 papers
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…
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…
Scalable Feature Subset Selection for Big Data using Parallel Hybrid Evolutionary Algorithm based Wrapper in Apache Spark
Yelleti Vivek, Vadlamani Ravi, Pisipati Radhakrishna
Owing to the emergence of large datasets, applying current sequential wrapper-based feature subset selection (FSS) algorithms increases the complexity. This limitation motivated us…