122 citations · 239 across the 37 of their papers we have counts for
11 papers · 1 filter
Multiple Perturbation Attack: Attack Pixelwise Under Different -norms For Better Adversarial Performance
Ngoc N. Tran, Anh Tuan Bui, Dinh Phung +1
Adversarial machine learning has been both a major concern and a hot topic recently, especially with the ubiquitous use of deep neural networks in the current landscape. Adversaria…
An Optimal Transport-driven Approach for Cultivating Latent Space in Online Incremental Learning
Quyen Tran, Hai Nguyen, Hoang Phan +6
In online incremental learning, data continuously arrives with substantial distributional shifts, creating a significant challenge because previous samples have limited replay valu…
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…
Vision Transformer Visualization: What Neurons Tell and How Neurons Behave?
Van-Anh Nguyen, Khanh Pham Dinh, Long Tung Vuong +4
Recently vision transformers (ViT) have been applied successfully for various tasks in computer vision. However, important questions such as why they work or how they behave still…
Cross Project Software Vulnerability Detection via Domain Adaptation and Max-Margin Principle
Van Nguyen, Trung Le, Chakkrit Tantithamthavorn +3
Software vulnerabilities (SVs) have become a common, serious and crucial concern due to the ubiquity of computer software. Many machine learning-based approaches have been proposed…
Feature-based Learning for Diverse and Privacy-Preserving Counterfactual Explanations
Vy Vo, Trung Le, Van Nguyen +4
Interpretable machine learning seeks to understand the reasoning process of complex black-box systems that are long notorious for lack of explainability. One flourishing approach i…