Search Results for author:
Found 7 papers, 3 papers with code
Data Distribution-based Curriculum Learning
Curriculum learning is a method of ordering training samples from easy to hard.
SMOTified-GAN for class imbalanced pattern classification problems
The experimental results prove the sample quality of minority class(es) has been improved in a variety of tested benchmark datasets.
Guided parallelized stochastic gradient descent for delay compensation
The experimental results demonstrate that our proposed approach has been able to mitigate the impact of delay for the quality of classification accuracy.
Optimistic variants of single-objective bilevel optimization for evolutionary algorithms
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.
Classification with 2-D Convolutional Neural Networks for breast cancer diagnosis
We tested our methods on Wisconsin Original Breast Cancer (WBC) and Wisconsin Diagnostic Breast Cancer (WDBC) datasets.
A Constraint Driven Solution Model for Discrete Domains with a Case Study of Exam Timetabling Problems
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.
Stacked transfer learning for tropical cyclone intensity prediction
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.
