no code implementations • 12 Feb 2024 • Shonal Chaudhry, Anuraganand Sharma
Curriculum learning is a method of ordering training samples from easy to hard.
1 code implementation • 6 Aug 2021 • Anuraganand Sharma, Prabhat Kumar Singh, Rohitash Chandra
The experimental results prove the sample quality of minority class(es) has been improved in a variety of tested benchmark datasets.
no code implementations • 17 Jan 2021 • Anuraganand Sharma
The experimental results demonstrate that our proposed approach has been able to mitigate the impact of delay for the quality of classification accuracy.
1 code implementation • 22 Aug 2020 • Anuraganand Sharma
In this work, a partial nested evolutionary approach with a local heuristic search has been proposed to solve the benchmark problems and have outstanding results.
1 code implementation • 7 Jul 2020 • Anuraganand Sharma, Dinesh Kumar
We tested our methods on Wisconsin Original Breast Cancer (WBC) and Wisconsin Diagnostic Breast Cancer (WDBC) datasets.
no code implementations • 8 Feb 2020 • Anuraganand Sharma
Evolutionary algorithms (EAs) are good solvers for optimization problems ubiquitous in various problem domains, however traditional operators for EAs are 'blind' to constraints or generally use problem dependent objective functions; as they do not exploit information from the constraints in search for solutions.
no code implementations • 22 Aug 2017 • Ratneel Vikash Deo, Rohitash Chandra, Anuraganand Sharma
In this paper, we employ transfer stacking as a means of studying the effects of cyclones whereby we evaluate if cyclones in different geographic locations can be helpful for improving generalization performs.