no code implementations • 19 Jan 2024 • Yanyong Huang, Zongxin Shen, Tianrui Li, Fengmao Lv
UNIFIER explores the local structure of multi-view data by adaptively learning similarity-induced graphs from both the sample and feature spaces.
no code implementations • 26 Sep 2022 • Dongjie Wang, Kunpeng Liu, Yanyong Huang, Leilei Sun, Bowen Du, Yanjie Fu
While automated urban planners have been examined, they are constrained because of the following: 1) neglecting human requirements in urban planning; 2) omitting spatial hierarchies in urban planning, and 3) lacking numerous urban plan data samples.
no code implementations • 20 Aug 2022 • Yanyong Huang, Zongxin Shen, Yuxin Cai, Xiuwen Yi, Dongjie Wang, Fengmao Lv, Tianrui Li
Besides, learning the complete similarity graph, as an important promising technology in existing MUFS methods, cannot achieve due to the missing views.
no code implementations • 5 Apr 2022 • Yanyong Huang, Kejun Guo, Xiuwen Yi, Zhong Li, Tianrui Li
To address these issues, we propose an Incremental Incomplete Multi-view Unsupervised Feature Selection method (I$^2$MUFS) on incomplete multi-view streaming data.
no code implementations • 2 Dec 2021 • Huaishao Luo, Lei Ji, Yanyong Huang, Bin Wang, Shenggong Ji, Tianrui Li
This paper proposes a fusion model named ScaleVLAD to gather multi-Scale representation from text, video, and audio with shared Vectors of Locally Aggregated Descriptors to improve unaligned multimodal sentiment analysis.
no code implementations • CVPR 2021 • Fengmao Lv, Xiang Chen, Yanyong Huang, Lixin Duan, Guosheng Lin
In turn, it also collects the reinforced features from each modality and uses them to generate a reinforced common message.
no code implementations • 27 Dec 2020 • Yanyong Huang, Zongxin Shen, Fuxu Cai, Tianrui Li, Fengmao Lv
Other existing methods choose the discriminative features with low redundancy by constructing the graph matrix on the original feature space.