7 accepted papers
Adversarial perturbations (APs) have become a great concern in image classification tasks. The most challenging branch, universal adversarial perturbations (UAPs), are exploited to fool most of the unseen samples. Such one-to-all perturbations have the merit of transferability, which has strong prac
Vision-Language Retrieval-Augmented Generation (VLRAG) systems have been widely applied to Large Vision-Language Models (LVLMs) to enhance their generation ability. However, the reliance on external multimodal knowledge databases renders VLRAG systems vulnerable to malicious poisoning attacks. In th…
While deep learning models have shown significant performance across various domains, their deployment needs extensive resources and advanced computing infrastructure. As a solution, Machine Learning as a Service (MLaaS) has emerged, lowering the barriers for users to release or productize their dee…
Machine unlearning can fortify the privacy and security of machine learning applications. Unfortunately, the exact unlearning approaches are inefficient, and the approximate unlearning approaches are unsuitable for complicated CNNs. Moreover, the approximate approaches have serious security flaws be…
Adversarial training (AT) is the most commonly used mechanism to improve the robustness of deep neural networks. Recently, a novel adversarial attack against intermediate layers exploits the extra fragility of adversarially trained networks to output incorrect predictions. The result implies the ins…
Relation Classification (RC) plays an important role in natural language processing (NLP). Current conventional supervised and distantly supervised RC models always make a closed-world assumption which ignores the emergence of novel relations in open environment. To incrementally recognize the novel…
Moments are a kind of classical feature descriptors for image analysis. Orthogonal moments, due to their computation efficiency and numerical stability, have been widely developed. We propose a set of orthogonal polynomials which are derived from the parity of Hermite polynomials. The new orthogonal…