1 citations · 1 across the 3 of their papers we have counts for
10 papers
No-Free-Fairness: Fundamental Limits and Trade-offs in Learning Systems
Khoat Than
In this paper, we establish a set of theoretical impossibility results, termed the No-Free-Fairness theorems, that identify three fundamental sources of disparity in learning syste…
Enhancing Visual Feature Attribution via Weighted Integrated Gradients
Kien Tran Duc Tuan, Tam Nguyen Trong, Son Nguyen Hoang +2
Integrated Gradients (IG) is a widely used attribution method in explainable AI, particularly in computer vision applications where reliable feature attribution is essential. A key…
High-Dimensional Random Projection for Activation Steering in Language Models
Minh-Hieu Pham, Bach Do, Laziz Abdullaev +2
Activation steering has emerged as a key methodology for controlling the behavior of large language models (LLMs). Existing difference-in-means based methods, however, are fundamen…
Non-vacuous Generalization Bounds for Deep Neural Networks without any modification to the trained models
Khoat Than, Dat Phan
Understanding and certifying the behavior of modern deep neural networks remains a fundamental challenge in reliable machine learning. We introduce a new class of data-dependent ge…
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…
LCA: Local Classifier Alignment for Continual Learning
Tung Tran, Danilo Vasconcellos Vargas, Khoat Than
A fundamental requirement for intelligent systems is the ability to learn continuously under changing environments. However, models trained in this regime often suffer from catastr…