10 citations · 11 across the 5 of their papers we have counts for
5 papers
Reinforcement Learning based Workflow Scheduling in Cloud and Edge Computing Environments: A Taxonomy, Review and Future Directions
Amanda Jayanetti, Saman Halgamuge, Rajkumar Buyya
Deep Reinforcement Learning (DRL) techniques have been successfully applied for solving complex decision-making and control tasks in multiple fields including robotics, autonomous…
A Deep Reinforcement Learning Approach for Cost Optimized Workflow Scheduling in Cloud Computing Environments
Amanda Jayanetti, Saman Halgamuge, Rajkumar Buyya
Cost optimization is a common goal of workflow schedulers operating in cloud computing environments. The use of spot instances is a potential means of achieving this goal, as they…
Discriminative Sample-Guided and Parameter-Efficient Feature Space Adaptation for Cross-Domain Few-Shot Learning
Rashindrie Perera, Saman Halgamuge
In this paper, we look at cross-domain few-shot classification which presents the challenging task of learning new classes in previously unseen domains with few labelled examples.…
Undercover Deepfakes: Detecting Fake Segments in Videos
Sanjay Saha, Rashindrie Perera, Sachith Seneviratne +5
The recent renaissance in generative models, driven primarily by the advent of diffusion models and iterative improvement in GAN methods, has enabled many creative applications. Ho…
Interpretability and accessibility of machine learning in selected food processing, agriculture and health applications
N. Ranasinghe, A. Ramanan, S. Fernando +6
Artificial Intelligence (AI) and its data-centric branch of machine learning (ML) have greatly evolved over the last few decades. However, as AI is used increasingly in real world…