no code implementations • 29 Mar 2023 • Xue Zaifa, Lu Huibin, Zhang Tao, Li Tao, Lu Xin
In this paper, we propose the method named three-way causal attribute partial order structure (3WCAPOS) to evolve the POFSA from set coverage to causal coverage in order to increase the interpretability and classification performance of the model.
no code implementations • 12 Nov 2022 • Jiayun Wu, Tao Jia, Yansong Wang, Li Tao
To better model the diversity of interactions, STGNN introduces a novel aggregation mechanism to organize the most significant historical neighbors' information and adaptively obtain the significance of node pairs.
1 code implementation • 29 Oct 2020 • Li Tao, Xueting Wang, Toshihiko Yamasaki
It is convenient to treat PCL as a standard training strategy and apply it to many other works in self-supervised video feature learning.
Ranked #10 on Self-supervised Video Retrieval on UCF101
2 code implementations • 6 Aug 2020 • Li Tao, Xueting Wang, Toshihiko Yamasaki
With the proposed Inter-Intra Contrastive (IIC) framework, we can train spatio-temporal convolutional networks to learn video representations.
Ranked #10 on Self-supervised Video Retrieval on HMDB51
3 code implementations • 21 Jun 2020 • Li Tao, Xueting Wang, Toshihiko Yamasaki
In this paper, we propose a fast but effective way to extract motion features from videos utilizing residual frames as the input data in 3D ConvNets.
3 code implementations • 16 Jan 2020 • Li Tao, Xueting Wang, Toshihiko Yamasaki
Further analysis indicates that better motion features can be extracted using residual frames with 3D ConvNets, and our residual-frame-input path is a good supplement for existing RGB-frame-input models.
no code implementations • 12 Jan 2020 • Yiyan Chen, Li Tao, Xueting Wang, Toshihiko Yamasaki
For each subtask, the manager is trained to set a subgoal only by a task-level binary label, which requires much fewer labels than conventional approaches.
Hierarchical Reinforcement Learning reinforcement-learning +2
no code implementations • 27 Sep 2018 • Li Tao, Choi Minsoo, Fu Kaiming, Lin Lei
Recommendation systems that automatically generate personalized music playlists for users have attracted tremendous attention in recent years.
no code implementations • 20 Dec 2017 • Baral Ramesh, Li Tao
The major contributions of this paper are: (i) it models users and locations based on the aspects posted by user via reviews, (ii) it exploits a deep neural network to model the review-aspect category correlation, (iii) it provisions the incorporation of multiple contexts (e. g., categorical, spatial, etc.)