11 citations · 33 across the 13 of their papers we have counts for
14 papers
Synthesizing Physical Backdoor Datasets: An Automated Framework Leveraging Deep Generative Models
Sze Jue Yang, Chinh D. La, Quang H. Nguyen +4
Backdoor attacks, representing an emerging threat to the integrity of deep neural networks, have garnered significant attention due to their ability to compromise deep learning sys…
Fooling the Textual Fooler via Randomizing Latent Representations
Duy C. Hoang, Quang H. Nguyen, Saurav Manchanda +3
Despite outstanding performance in a variety of NLP tasks, recent studies have revealed that NLP models are vulnerable to adversarial attacks that slightly perturb the input to cau…
Understanding the Robustness of Randomized Feature Defense Against Query-Based Adversarial Attacks
Quang H. Nguyen, Yingjie Lao, Tung Pham +2
Recent works have shown that deep neural networks are vulnerable to adversarial examples that find samples close to the original image but can make the model misclassify. Even with…
Everyone Can Attack: Repurpose Lossy Compression as a Natural Backdoor Attack
Sze Jue Yang, Quang Nguyen, Chee Seng Chan +1
The vulnerabilities to backdoor attacks have recently threatened the trustworthiness of machine learning models in practical applications. Conventional wisdom suggests that not eve…
Backdoor Attacks and Defenses in Federated Learning: Survey, Challenges and Future Research Directions
Thuy Dung Nguyen, Tuan Nguyen, Phi Le Nguyen +3
Federated learning (FL) is a machine learning (ML) approach that allows the use of distributed data without compromising personal privacy. However, the heterogeneous distribution o…
Asymmetric Hashing for Fast Ranking via Neural Network Measures
Khoa Doan, Shulong Tan, Weijie Zhao +1
Fast item ranking is an important task in recommender systems. In previous works, graph-based Approximate Nearest Neighbor (ANN) approaches have demonstrated good performance on it…
Marksman Backdoor: Backdoor Attacks with Arbitrary Target Class
Khoa D. Doan, Yingjie Lao, Ping Li
In recent years, machine learning models have been shown to be vulnerable to backdoor attacks. Under such attacks, an adversary embeds a stealthy backdoor into the trained model su…
CoopHash: Cooperative Learning of Multipurpose Descriptor and Contrastive Pair Generator via Variational MCMC Teaching for Supervised Image Hashing
Khoa D. Doan, Jianwen Xie, Yaxuan Zhu +2
Leveraging supervised information can lead to superior retrieval performance in the image hashing domain but the performance degrades significantly without enough labeled data. One…
Defending Backdoor Attacks on Vision Transformer via Patch Processing
Khoa D. Doan, Yingjie Lao, Peng Yang +1
Vision Transformers (ViTs) have a radically different architecture with significantly less inductive bias than Convolutional Neural Networks. Along with the improvement in performa…
One Loss for Quantization: Deep Hashing with Discrete Wasserstein Distributional Matching
Khoa D. Doan, Peng Yang, Ping Li
Image hashing is a principled approximate nearest neighbor approach to find similar items to a query in a large collection of images. Hashing aims to learn a binary-output function…
Image Generation Via Minimizing Fréchet Distance in Discriminator Feature Space
Khoa D. Doan, Saurav Manchanda, Fengjiao Wang +3
For a given image generation problem, the intrinsic image manifold is often low dimensional. We use the intuition that it is much better to train the GAN generator by minimizing th…
Regression via Implicit Models and Optimal Transport Cost Minimization
Saurav Manchanda, Khoa Doan, Pranjul Yadav +1
This paper addresses the classic problem of regression, which involves the inductive learning of a map, , denoting noise, $f:\mathbb{R}^n\times \mathbb{R}^k \rightarr…
Image Hashing by Minimizing Discrete Component-wise Wasserstein Distance
Khoa D. Doan, Saurav Manchanda, Sarkhan Badirli +1
Image hashing is one of the fundamental problems that demand both efficient and effective solutions for various practical scenarios. Adversarial autoencoders are shown to be able t…
Targeted display advertising: the case of preferential attachment
Saurav Manchanda, Pranjul Yadav, Khoa Doan +1
An average adult is exposed to hundreds of digital advertisements daily (https://www.mediadynamicsinc.com/uploads/files/PR092214-Note-only-150-Ads-2mk.pdf), making the digital adve…