Zobrazeno 1 - 10
of 201
pro vyhledávání: '"YANG Xihong"'
Autor:
Yang, Xihong, Jing, Heming, Zhang, Zixing, Wang, Jindong, Niu, Huakang, Wang, Shuaiqiang, Lu, Yu, Wang, Junfeng, Yin, Dawei, Liu, Xinwang, Zhu, En, Lian, Defu, Min, Erxue
Benefiting from the strong reasoning capabilities, Large language models (LLMs) have demonstrated remarkable performance in recommender systems. Various efforts have been made to distill knowledge from LLMs to enhance collaborative models, employing
Externí odkaz:
http://arxiv.org/abs/2408.08231
Autor:
Yang, Xihong, Wang, Yiqi, Chen, Jin, Fan, Wenqi, Zhao, Xiangyu, Zhu, En, Liu, Xinwang, Lian, Defu
Deep learning has been widely applied in recommender systems, which has achieved revolutionary progress recently. However, most existing learning-based methods assume that the user and item distributions remain unchanged between the training phase an
Externí odkaz:
http://arxiv.org/abs/2407.15620
Autor:
Zhang, Jiaxin, Wang, Yiqi, Yang, Xihong, Wang, Siwei, Feng, Yu, Shi, Yu, Ren, Ruicaho, Zhu, En, Liu, Xinwang
Graph Neural Networks have demonstrated great success in various fields of multimedia. However, the distribution shift between the training and test data challenges the effectiveness of GNNs. To mitigate this challenge, Test-Time Training (TTT) has b
Externí odkaz:
http://arxiv.org/abs/2404.13571
In unsupervised scenarios, deep contrastive multi-view clustering (DCMVC) is becoming a hot research spot, which aims to mine the potential relationships between different views. Most existing DCMVC algorithms focus on exploring the consistency infor
Externí odkaz:
http://arxiv.org/abs/2309.00474
Autor:
Wen, Yi, Liu, Suyuan, Wan, Xinhang, Wang, Siwei, Liang, Ke, Liu, Xinwang, Yang, Xihong, Zhang, Pei
Anchor-based multi-view graph clustering (AMVGC) has received abundant attention owing to its high efficiency and the capability to capture complementary structural information across multiple views. Intuitively, a high-quality anchor graph plays an
Externí odkaz:
http://arxiv.org/abs/2309.00024
Autor:
Yang, Xihong, Jin, Jiaqi, Wang, Siwei, Liang, Ke, Liu, Yue, Wen, Yi, Liu, Suyuan, Zhou, Sihang, Liu, Xinwang, Zhu, En
Benefiting from the strong view-consistent information mining capacity, multi-view contrastive clustering has attracted plenty of attention in recent years. However, we observe the following drawback, which limits the clustering performance from furt
Externí odkaz:
http://arxiv.org/abs/2308.09000
Autor:
Yang, Xihong, Tan, Cheng, Liu, Yue, Liang, Ke, Wang, Siwei, Zhou, Sihang, Xia, Jun, Li, Stan Z., Liu, Xinwang, Zhu, En
Contrastive graph node clustering via learnable data augmentation is a hot research spot in the field of unsupervised graph learning. The existing methods learn the sampling distribution of a pre-defined augmentation to generate data-driven augmentat
Externí odkaz:
http://arxiv.org/abs/2308.08963
Autor:
Liu, Yue, Liang, Ke, Xia, Jun, Yang, Xihong, Zhou, Sihang, Liu, Meng, Liu, Xinwang, Li, Stan Z.
Deep graph clustering, which aims to group nodes into disjoint clusters by neural networks in an unsupervised manner, has attracted great attention in recent years. Although the performance has been largely improved, the excellent performance of the
Externí odkaz:
http://arxiv.org/abs/2308.06827
Deep graph clustering, which aims to group the nodes of a graph into disjoint clusters with deep neural networks, has achieved promising progress in recent years. However, the existing methods fail to scale to the large graph with million nodes. To s
Externí odkaz:
http://arxiv.org/abs/2305.18405
Autor:
Tan, Cheng, Gao, Zhangyang, Wu, Lirong, Xia, Jun, Zheng, Jiangbin, Yang, Xihong, Liu, Yue, Hu, Bozhen, Li, Stan Z.
Antibodies are crucial proteins produced by the immune system in response to foreign substances or antigens. The specificity of an antibody is determined by its complementarity-determining regions (CDRs), which are located in the variable domains of
Externí odkaz:
http://arxiv.org/abs/2305.09480