2 citations · 2 across the 4 of their papers we have counts for
5 papers
Tree SAE: Learning Hierarchical Feature Structures in Sparse Autoencoders
Tue M. Cao, Hoang X. Nhat, Raed Alharbi +2
Learning hierarchical features in Sparse Autoencoders (SAEs) is essential for capturing the structured nature of real-world data and mitigating issues like feature absorption or sp…
Swift Hydra: Self-Reinforcing Generative Framework for Anomaly Detection with Multiple Mamba Models
Nguyen Do, Truc Nguyen, Malik Hassanaly +3
Despite a plethora of anomaly detection models developed over the years, their ability to generalize to unseen anomalies remains an issue, particularly in critical systems. This pa…
OASIS: Offsetting Active Reconstruction Attacks in Federated Learning
Tre' R. Jeter, Truc Nguyen, Raed Alharbi +1
Federated Learning (FL) has garnered significant attention for its potential to protect user privacy while enhancing model training efficiency. For that reason, FL has found its us…
Cultural-aware Machine Learning based Analysis of COVID-19 Vaccine Hesitancy
Raed Alharbi, Sylvia Chan-Olmsted, Huan Chen +1
Understanding the COVID-19 vaccine hesitancy, such as who and why, is very crucial since a large-scale vaccine adoption remains as one of the most efficient methods of controlling…
Learning Interpretation with Explainable Knowledge Distillation
Raed Alharbi, Minh N. Vu, My T. Thai
Knowledge Distillation (KD) has been considered as a key solution in model compression and acceleration in recent years. In KD, a small student model is generally trained from a la…