15 citations · 29 across the 13 of their papers we have counts for
5 papers · 1 filter
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…
Parallel and Streaming Wavelet Neural Networks for Classification and Regression under Apache Spark
Eduru Harindra Venkatesh, Yelleti Vivek, Vadlamani Ravi +1
Wavelet neural networks (WNN) have been applied in many fields to solve regression as well as classification problems. After the advent of big data, as data gets generated at a bri…
Feature subset selection for Big Data via Chaotic Binary Differential Evolution under Apache Spark
Yelleti Vivek, Vadlamani Ravi, P. Radhakrishna
Feature subset selection (FSS) using a wrapper approach is essentially a combinatorial optimization problem having two objective functions namely cardinality of the selected-featur…
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…