5 papers
PBP: Post-training Backdoor Purification for Malware Classifiers
Dung Thuy Nguyen, Ngoc N. Tran, Taylor T. Johnson +1
In recent years, the rise of machine learning (ML) in cybersecurity has brought new challenges, including the increasing threat of backdoor poisoning attacks on ML malware classifi…
Quantifying the Generalization Gap: A New Benchmark for Out-of-Distribution Graph-Based Android Malware Classification
Ngoc N. Tran, Anwar Said, Waseem Abbas +2
While graph-based Android malware classifiers achieve over 94% accuracy on standard benchmarks, they exhibit a significant generalization gap under distribution shift, suffering up…
Generalization Bounds for Robust Contrastive Learning: From Theory to Practice
Ngoc N. Tran, Lam Tran, Hoang Phan +5
Contrastive Learning first extracts features from unlabeled data, followed by linear probing with labeled data. Adversarial Contrastive Learning (ACL) integrates Adversarial Traini…
Beyond Losses Reweighting: Empowering Multi-Task Learning via the Generalization Perspective
Hoang Phan, Lam Tran, Quyen Tran +6
Multi-task learning (MTL) trains deep neural networks to optimize several objectives simultaneously using a shared backbone, which leads to reduced computational costs, improved da…
Improving Routing in Sparse Mixture of Experts with Graph of Tokens
Tam Nguyen, Ngoc N. Tran, Khai Nguyen +1
Sparse Mixture of Experts (SMoE) has emerged as a key to achieving unprecedented scalability in deep learning. By activating only a small subset of parameters per sample, SMoE achi…