46 citations · 115 across the 36 of their papers we have counts for
6 papers · 1 filter
Resource-Efficient Multiview Perception: Integrating Semantic Masking with Masked Autoencoders
Kosta Dakic, Kanchana Thilakarathna, Rodrigo N. Calheiros +1
Multiview systems have become a key technology in modern computer vision, offering advanced capabilities in scene understanding and analysis. However, these systems face critical c…
SHFL: Secure Hierarchical Federated Learning Framework for Edge Networks
Omid Tavallaie, Kanchana Thilakarathna, Suranga Seneviratne +2
Federated Learning (FL) is a distributed machine learning paradigm designed for privacy-sensitive applications that run on resource-constrained devices with non-Identically and Ind…
ACCESS-FL: Agile Communication and Computation for Efficient Secure Aggregation in Stable Federated Learning Networks
Niousha Nazemi, Omid Tavallaie, Shuaijun Chen +5
Federated Learning (FL) is a promising distributed learning framework designed for privacy-aware applications. FL trains models on client devices without sharing the client's data…
TripletViNet: Mitigating Misinformation Video Spread Across Platforms
Petar Smolovic, Thilini Dahanayaka, Kanchana Thilakarathna
There has been rampant propagation of fake news and misinformation videos on many platforms lately, and moderation of such content faces many challenges that must be overcome. Rece…
CAFe: Cost and Age aware Federated Learning
Sahan Liyanaarachchi, Kanchana Thilakarathna, Sennur Ulukus
In many federated learning (FL) models, a common strategy employed to ensure the progress in the training process, is to wait for at least clients out of the total clients…
The Frontier of Data Erasure: Machine Unlearning for Large Language Models
Youyang Qu, Ming Ding, Nan Sun +3
Large Language Models (LLMs) are foundational to AI advancements, facilitating applications like predictive text generation. Nonetheless, they pose risks by potentially memorizing…