1 code implementation • 23 Apr 2024 • Thanh Toan Nguyen, Quoc Viet Hung Nguyen, Thanh Tam Nguyen, Thanh Trung Huynh, Thanh Thi Nguyen, Matthias Weidlich, Hongzhi Yin
This survey aims to fill this gap by primarily focusing on poisoning attacks and their countermeasures.
1 code implementation • 31 Mar 2024 • Thanh Tam Nguyen, Thanh Trung Huynh, Zhao Ren, Thanh Toan Nguyen, Phi Le Nguyen, Hongzhi Yin, Quoc Viet Hung Nguyen
As the adoption of explainable AI (XAI) continues to expand, the urgency to address its privacy implications intensifies.
no code implementations • 29 Mar 2024 • Wei Yuan, Chaoqun Yang, Liang Qu, Guanhua Ye, Quoc Viet Hung Nguyen, Hongzhi Yin
In this paper, we introduce a novel contrastive learning framework designed to fully leverage the client's sparse data through embedding augmentation, referred to as CL4FedRec.
no code implementations • 25 Dec 2023 • Lijian Chen, Wei Yuan, Tong Chen, Guanhua Ye, Quoc Viet Hung Nguyen, Hongzhi Yin
Visually-aware recommender systems have found widespread application in domains where visual elements significantly contribute to the inference of users' potential preferences.
1 code implementation • 25 Nov 2023 • Wei Yuan, Chaoqun Yang, Liang Qu, Quoc Viet Hung Nguyen, JianXin Li, Hongzhi Yin
Existing FedRecs generally adhere to a learning protocol in which a central server shares a global recommendation model with clients, and participants achieve collaborative learning by frequently communicating the model's public parameters.
no code implementations • 23 Oct 2023 • Yunke Qu, Tong Chen, Quoc Viet Hung Nguyen, Hongzhi Yin
Experiments have shown state-of-the-art performance on two real-world datasets when BET is paired with three popular recommender models under different memory budgets.
no code implementations • 17 Oct 2023 • Xinyi Gao, Wentao Zhang, Junliang Yu, Yingxia Shao, Quoc Viet Hung Nguyen, Bin Cui, Hongzhi Yin
To further accelerate Scalable GNNs inference in this inductive setting, we propose an online propagation framework and two novel node-adaptive propagation methods that can customize the optimal propagation depth for each node based on its topological information and thereby avoid redundant feature propagation.
1 code implementation • 7 Sep 2023 • Xurong Liang, Tong Chen, Quoc Viet Hung Nguyen, JianXin Li, Hongzhi Yin
In addition, we innovatively design a regularized pruning mechanism in CERP, such that the two sparsified meta-embedding tables are encouraged to encode information that is mutually complementary.
no code implementations • 25 Aug 2023 • Guanhua Ye, Tong Chen, Quoc Viet Hung Nguyen, Hongzhi Yin
As some recent information security legislation endowed users with unconditional rights to be forgotten by any trained machine learning model, personalized IoT service providers have to put unlearning functionality into their consideration.
no code implementations • 29 Jul 2023 • Xinyi Gao, Tong Chen, Yilong Zang, Wentao Zhang, Quoc Viet Hung Nguyen, Kai Zheng, Hongzhi Yin
To overcome this issue, we propose mapping-aware graph condensation (MCond), explicitly learning the one-to-many node mapping from original nodes to synthetic nodes to seamlessly integrate new nodes into the synthetic graph for inductive representation learning.
1 code implementation • 26 Jun 2023 • Zicheng Zhao, Linhao Luo, Shirui Pan, Quoc Viet Hung Nguyen, Chen Gong
Previous methods are limited to transductive scenarios, where entities exist in the knowledge graphs, so they are unable to handle unseen entities.
no code implementations • 17 Jun 2023 • Shangfei Zheng, Hongzhi Yin, Tong Chen, Quoc Viet Hung Nguyen, Wei Chen, Lei Zhao
This paper proposes a model called TMR to mine valuable information from simulated data environments.
1 code implementation • NeurIPS 2023 • Xin Zheng, Miao Zhang, Chunyang Chen, Quoc Viet Hung Nguyen, Xingquan Zhu, Shirui Pan
Specifically, SFGC contains two collaborative components: (1) a training trajectory meta-matching scheme for effectively synthesizing small-scale graph-free data; (2) a graph neural feature score metric for dynamically evaluating the quality of the condensed data.
no code implementations • 14 May 2023 • Wei Yuan, Shilong Yuan, Chaoqun Yang, Quoc Viet Hung Nguyen, Hongzhi Yin
Therefore, when incorporating visual information in FedRecs, all existing model poisoning attacks' effectiveness becomes questionable.
no code implementations • 1 May 2023 • Xuhui Ren, Tong Chen, Quoc Viet Hung Nguyen, Lizhen Cui, Zi Huang, Hongzhi Yin
Recent conversational recommender systems (CRSs) tackle those limitations by enabling recommender systems to interact with the user to obtain her/his current preference through a sequence of clarifying questions.
no code implementations • 24 Apr 2023 • Xuhui Ren, Wei Yuan, Tong Chen, Chaoqun Yang, Quoc Viet Hung Nguyen, Hongzhi Yin
Knowledge graphs (KGs) have become important auxiliary information for helping recommender systems obtain a good understanding of user preferences.
no code implementations • 8 Apr 2023 • Shangfei Zheng, Hongzhi Yin, Tong Chen, Quoc Viet Hung Nguyen, Wei Chen, Lei Zhao
Although existing TKG reasoning methods have the ability to predict missing future events, they fail to generate explicit reasoning paths and lack explainability.
no code implementations • 6 Apr 2023 • Wei Yuan, Quoc Viet Hung Nguyen, Tieke He, Liang Chen, Hongzhi Yin
To reveal the real vulnerability of FedRecs, in this paper, we present a new poisoning attack method to manipulate target items' ranks and exposure rates effectively in the top-$K$ recommendation without relying on any prior knowledge.
no code implementations • 17 Mar 2023 • Anh Duy Nguyen, Huy Hieu Pham, Huynh Thanh Trung, Quoc Viet Hung Nguyen, Thao Nguyen Truong, Phi Le Nguyen
We then offer a framework for integrating a priori with pills' visual features to enhance detection accuracy.
no code implementations • 7 Mar 2023 • Yuting Sun, Tong Chen, Quoc Viet Hung Nguyen, Hongzhi Yin
With the prevalent deployment of the Industrial Internet of Things (IIoT), an enormous amount of time series data is collected to facilitate machine learning models for anomaly detection, and it is of the utmost importance to directly deploy the trained models on the IIoT devices.
no code implementations • 10 Feb 2023 • Liang Qu, Ningzhi Tang, Ruiqi Zheng, Quoc Viet Hung Nguyen, Zi Huang, Yuhui Shi, Hongzhi Yin
In light of this, we propose a semi-decentralized federated ego graph learning framework for on-device recommendations, named SemiDFEGL, which introduces new device-to-device collaborations to improve scalability and reduce communication costs and innovatively utilizes predicted interacted item nodes to connect isolated ego graphs to augment local subgraphs such that the high-order user-item collaborative information could be used in a privacy-preserving manner.
no code implementations • 26 Jan 2023 • Wei Yuan, Chaoqun Yang, Quoc Viet Hung Nguyen, Lizhen Cui, Tieke He, Hongzhi Yin
An interaction-level membership inference attacker is first designed, and then the classical privacy protection mechanism, Local Differential Privacy (LDP), is adopted to defend against the membership inference attack.
1 code implementation • 11 Nov 2022 • Thanh Trung Huynh, Minh Hieu Nguyen, Thanh Tam Nguyen, Phi Le Nguyen, Matthias Weidlich, Quoc Viet Hung Nguyen, Karl Aberer
Advances in deep neural network (DNN) architectures have enabled new prediction techniques for stock market data.
no code implementations • 1 Nov 2022 • Xinyi Gao, Wentao Zhang, Yingxia Shao, Quoc Viet Hung Nguyen, Bin Cui, Hongzhi Yin
Graph neural networks (GNNs) have demonstrated excellent performance in a wide range of applications.
1 code implementation • 17 Oct 2022 • Vinh Tong, Dat Quoc Nguyen, Trung Thanh Huynh, Tam Thanh Nguyen, Quoc Viet Hung Nguyen, Mathias Niepert
The proposed model combines two components that jointly accomplish KG completion and alignment.
Ranked #1 on Knowledge Graph Completion on DPB-5L (French)
1 code implementation • 27 Sep 2022 • Xin Xia, Junliang Yu, Qinyong Wang, Chaoqun Yang, Quoc Viet Hung Nguyen, Hongzhi Yin
Specifically, each item is represented by a compositional code that consists of several codewords, and we learn embedding vectors to represent each codeword instead of each item.
1 code implementation • 6 Sep 2022 • Thanh Tam Nguyen, Thanh Trung Huynh, Phi Le Nguyen, Alan Wee-Chung Liew, Hongzhi Yin, Quoc Viet Hung Nguyen
Specifically, as a category collection of cutting-edge studies, the intention behind this article is to serve as a comprehensive resource for researchers and practitioners seeking an introduction to machine unlearning and its formulations, design criteria, removal requests, algorithms, and applications.
no code implementations • 17 Jul 2022 • Thanh Tam Nguyen, Thanh Cong Phan, Minh Hieu Nguyen, Matthias Weidlich, Hongzhi Yin, Jun Jo, Quoc Viet Hung Nguyen
Since the spread of rumours in social media is commonly modelled using feature-annotated graphs, we propose a query-by-example approach that, given a rumour graph, extracts the $k$ most similar and diverse subgraphs from past rumours.
no code implementations • 1 Jul 2022 • Yu Yang, Hongzhi Yin, Jiannong Cao, Tong Chen, Quoc Viet Hung Nguyen, Xiaofang Zhou, Lei Chen
Meanwhile, we treat each edge sequence as a whole and embed its ToV of the first vertex to further encode the time-sensitive information.
no code implementations • 13 May 2022 • Thanh Tam Nguyen, Thanh Trung Huynh, Hongzhi Yin, Matthias Weidlich, Thanh Thi Nguyen, Thai Son Mai, Quoc Viet Hung Nguyen
Today's social networks continuously generate massive streams of data, which provide a valuable starting point for the detection of rumours as soon as they start to propagate.
1 code implementation • 6 Apr 2022 • Tong Chen, Hongzhi Yin, Jing Long, Quoc Viet Hung Nguyen, Yang Wang, Meng Wang
Such user and group preferences are commonly represented as points in the vector space (i. e., embeddings), where multiple user embeddings are compressed into one to facilitate ranking for group-item pairs.
no code implementations • 17 Dec 2021 • Guanhua Ye, Hongzhi Yin, Tong Chen, Miao Xu, Quoc Viet Hung Nguyen, Jiangning Song
Actuated by the growing attention to personal healthcare and the pandemic, the popularity of E-health is proliferating.
no code implementations • 17 Dec 2021 • Vinh Van Tong, Thanh Trung Huynh, Thanh Tam Nguyen, Hongzhi Yin, Quoc Viet Hung Nguyen, Quyet Thang Huynh
Our KG embedding framework exploits two feature channels: transitivity-based and proximity-based.
1 code implementation • 16 Dec 2021 • Junliang Yu, Hongzhi Yin, Xin Xia, Tong Chen, Lizhen Cui, Quoc Viet Hung Nguyen
Contrastive learning (CL) recently has spurred a fruitful line of research in the field of recommendation, since its ability to extract self-supervised signals from the raw data is well-aligned with recommender systems' needs for tackling the data sparsity issue.
1 code implementation • 25 Nov 2021 • Minh Tam Pham, Thanh Trung Huynh, Van Vinh Tong, Thanh Tam Nguyen, Thanh Thi Nguyen, Hongzhi Yin, Quoc Viet Hung Nguyen
In recent years, visual forgery has reached a level of sophistication that humans cannot identify fraud, which poses a significant threat to information security.
no code implementations • 21 Oct 2021 • Shijie Zhang, Hongzhi Yin, Tong Chen, Zi Huang, Quoc Viet Hung Nguyen, Lizhen Cui
Evaluations on two real-world datasets show that 1) our attack model significantly boosts the exposure rate of the target item in a stealthy way, without harming the accuracy of the poisoned recommender; and 2) existing defenses are not effective enough, highlighting the need for new defenses against our local model poisoning attacks to federated recommender systems.
no code implementations • 7 May 2021 • Lei Guo, Li Tang, Tong Chen, Lei Zhu, Quoc Viet Hung Nguyen, Hongzhi Yin
Shared-account Cross-domain Sequential recommendation (SCSR) is the task of recommending the next item based on a sequence of recorded user behaviors, where multiple users share a single account, and their behaviours are available in multiple domains.
1 code implementation • 17 Nov 2020 • Tam Thanh Nguyen, Thanh Trung Huynh, Hongzhi Yin, Vinh Van Tong, Darnbi Sakong, Bolong Zheng, Quoc Viet Hung Nguyen
Knowledge graphs (KGs) have become popular structures for unifying real-world entities by modelling the relationships between them and their attributes.
Ranked #7 on Entity Alignment on DBP15k zh-en (using extra training data)
no code implementations • 30 Jul 2020 • Thanh Thi Nguyen, Quoc Viet Hung Nguyen, Dung Tien Nguyen, Samuel Yang, Peter W. Eklund, Thien Huynh-The, Thanh Tam Nguyen, Quoc-Viet Pham, Imran Razzak, Edbert B. Hsu
Artificial intelligence (AI) has been applied widely in our daily lives in a variety of ways with numerous success stories.
no code implementations • 20 Nov 2019 • Chi Thang Duong, Thanh Dat Hoang, Ha The Hien Dang, Quoc Viet Hung Nguyen, Karl Aberer
Graph neural network (GNN) is a deep model for graph representation learning.
no code implementations • 7 Nov 2019 • Tong Chen, Hongzhi Yin, Quoc Viet Hung Nguyen, Wen-Chih Peng, Xue Li, Xiaofang Zhou
As a widely adopted solution, models based on Factorization Machines (FMs) are capable of modelling high-order interactions among features for effective sparse predictive analytics.
no code implementations • 25 Sep 2019 • Chi Thang Duong, Dung Hoang, Truong Giang Le Ba, Thanh Le Cong, Hongzhi Yin, Matthias Weidlich, Quoc Viet Hung Nguyen, Karl Aberer
We provide empirical evidence that the communities learned by DMC are meaningful and that the node embeddings are competitive in different node classification benchmarks.
no code implementations • 25 Sep 2019 • Thanh Thi Nguyen, Quoc Viet Hung Nguyen, Dung Tien Nguyen, Duc Thanh Nguyen, Thien Huynh-The, Saeid Nahavandi, Thanh Tam Nguyen, Quoc-Viet Pham, Cuong M. Nguyen
By reviewing the background of deepfakes and state-of-the-art deepfake detection methods, this study provides a comprehensive overview of deepfake techniques and facilitates the development of new and more robust methods to deal with the increasingly challenging deepfakes.
no code implementations • 6 Sep 2019 • Chi Thang Duong, Hongzhi Yin, Thanh Dat Hoang, Truong Giang Le Ba, Matthias Weidlich, Quoc Viet Hung Nguyen, Karl Aberer
We therefore propose a framework for parallel computation of a graph embedding using a cluster of compute nodes with resource constraints.