no code implementations • 18 Apr 2024 • Liang Qu, Yun Lin, Wei Yuan, Xiaojun Wan, Yuhui Shi, Hongzhi Yin
Given the critical role of similarity metrics in recommender systems, existing methods mainly employ handcrafted similarity metrics to capture the complex characteristics of user-item interactions.
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 • 31 Jan 2024 • Liang Qu, Wei Yuan, Ruiqi Zheng, Lizhen Cui, Yuhui Shi, Hongzhi Yin
To bridge this gap, this paper explores a user-governed data contribution federated recommendation architecture where users are free to take control of whether they share data and the proportion of data they share to the server.
no code implementations • 21 Jan 2024 • Hongzhi Yin, Liang Qu, Tong Chen, Wei Yuan, Ruiqi Zheng, Jing Long, Xin Xia, Yuhui Shi, Chengqi Zhang
Recently, driven by the advances in storage, communication, and computation capabilities of edge devices, there has been a shift of focus from CloudRSs to on-device recommender systems (DeviceRSs), which leverage the capabilities of edge devices to minimize centralized data storage requirements, reduce the response latency caused by communication overheads, and enhance user privacy and security by localizing data processing and model training.
no code implementations • 7 Jan 2024 • Shilong Yuan, Wei Yuan, Hongzhi Yin, Tieke He
While language models have made many milestones in text inference and classification tasks, they remain susceptible to adversarial attacks that can lead to unforeseen outcomes.
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 • 18 Nov 2023 • Yueyuan Li, Wei Yuan, Songan Zhang, Weihao Yan, Qiyuan Shen, Chunxiang Wang, Ming Yang
Simulators play a crucial role in autonomous driving, offering significant time, cost, and labor savings.
no code implementations • 24 Jul 2023 • Wei Yuan, Liang Qu, Lizhen Cui, Yongxin Tong, Xiaofang Zhou, Hongzhi Yin
Owing to the nature of privacy protection, federated recommender systems (FedRecs) have garnered increasing interest in the realm of on-device recommender systems.
no code implementations • 20 Jul 2023 • Weihang Ran, Wei Yuan, Xiaodan Shi, Zipei Fan, Ryosuke Shibasaki
Building outline extracted from high-resolution aerial images can be used in various application fields such as change detection and disaster assessment.
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.
1 code implementation • 11 May 2023 • Lingzhi Wang, Tong Chen, Wei Yuan, Xingshan Zeng, Kam-Fai Wong, Hongzhi Yin
Recent legislation of the "right to be forgotten" has led to the interest in machine unlearning, where the learned models are endowed with the function to forget information about specific training instances as if they have never existed in the training set.
no code implementations • CVPR 2023 • Zhibo Wang, He Wang, Shuaifan Jin, Wenwen Zhang, Jiahui Hu, Yan Wang, Peng Sun, Wei Yuan, Kaixin Liu, Kui Ren
In this paper, we propose an adversarial features-based face privacy protection (AdvFace) approach to generate privacy-preserving adversarial features, which can disrupt the mapping from adversarial features to facial images to defend against reconstruction attacks.
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 • 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 • 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.
no code implementations • 20 Oct 2022 • Wei Yuan, Hongzhi Yin, Fangzhao Wu, Shijie Zhang, Tieke He, Hao Wang
It removes a user's contribution by rolling back and calibrating the historical parameter updates and then uses these updates to speed up federated recommender reconstruction.
no code implementations • 7 Sep 2022 • Yuchen Gui, Boyi Wei, Wei Yuan, Xi Jin
Sampling is an important process in many GNN structures in order to train larger datasets with a smaller computational complexity.
no code implementations • 21 Jun 2022 • Zipei Fan, Xiaojie Yang, Wei Yuan, Renhe Jiang, Quanjun Chen, Xuan Song, Ryosuke Shibasaki
In the first stage, to encode the daily variation of human mobility at a metropolitan level, we automatically extract citywide mobility trends as crowd contexts and predict long-term and long-distance movements at a coarse level.
no code implementations • 24 May 2022 • Shijie Zhang, Wei Yuan, Hongzhi Yin
In this paper, we first design a novel attribute inference attacker to perform a comprehensive privacy analysis of the state-of-the-art federated recommender models.
no code implementations • 17 Feb 2022 • Beihao Xia, Conghao Wong, Qinmu Peng, Wei Yuan, Xinge You
The current methods are dedicated to studying the agents' future trajectories under the social interaction and the sceneries' physical constraints.
no code implementations • 24 Jan 2022 • Wei Yuan, Hongzhi Yin, Tieke He, Tong Chen, Qiufeng Wang, Lizhen Cui
To solve the problems, we propose a model named Unified-QG based on lifelong learning techniques, which can continually learn QG tasks across different datasets and formats.
1 code implementation • 14 Oct 2021 • Conghao Wong, Beihao Xia, Ziming Hong, Qinmu Peng, Wei Yuan, Qiong Cao, Yibo Yang, Xinge You
Different frequency bands in the trajectory spectrums could hierarchically reflect agents' motion preferences at different scales.
Ranked #3 on Trajectory Prediction on ETH/UCY
1 code implementation • 2 Jul 2021 • Conghao Wong, Beihao Xia, Qinmu Peng, Wei Yuan, Xinge You
Then, we assume that the target agents may plan their future behaviors according to each of these categorized styles, thus utilizing different style channels to make predictions with significant style differences in parallel.
1 code implementation • 10 Jun 2021 • Hezheng Lin, Xing Cheng, Xiangyu Wu, Fan Yang, Dong Shen, Zhongyuan Wang, Qing Song, Wei Yuan
In this paper, we propose a new attention mechanism in Transformer termed Cross Attention, which alternates attention inner the image patch instead of the whole image to capture local information and apply attention between image patches which are divided from single-channel feature maps capture global information.
no code implementations • 11 Feb 2021 • Yueh-Ju Lin, Wei Yuan
This is the second article of a sequence of research on deformations of Q-curvature.
Differential Geometry
2 code implementations • 4 Nov 2020 • Wei Yuan, Kai-Xin Gao
Recently, many variants of Adam, such as Adabound, RAdam and Adabelief, have been proposed and show better performance than Adam.
1 code implementation • 11 Nov 2019 • Shiming Chen, Peng Zhang, Guo-Sen Xie, Qinmu Peng, Zehong Cao, Wei Yuan, Xinge You
Dynamic texture (DT) exhibits statistical stationarity in the spatial domain and stochastic repetitiveness in the temporal dimension, indicating that different frames of DT possess a high similarity correlation that is critical prior knowledge.
no code implementations • 28 Sep 2018 • Zhiling Guo, Hiroaki Shengoku, Guangming Wu, Qi Chen, Wei Yuan, Xiaodan Shi, Xiaowei Shao, Yongwei Xu, Ryosuke Shibasaki
The results indicate the proposed method can serve as a viable tool for urban planning map semantic segmentation task with high accuracy and efficiency.
no code implementations • 14 May 2018 • Xinge You, Jiamiao Xu, Wei Yuan, Xiao-Yuan Jing, DaCheng Tao, Taiping Zhang
Cross-view classification that means to classify samples from heterogeneous views is a significant yet challenging problem in computer vision.
no code implementations • 4 Mar 2015 • Zi Wang, Wei Yuan, Giovanni Montana
The proposed methodology can be interpreted as an extension of principal component analysis in that it provides the means to decompose the total sample variance in each tissue into the sum of two components: one capturing the variance that is shared across tissues, and one isolating the tissue-specific variances.