Search Results for author: Li Tao

Found 13 papers, 5 papers with code

PERS: A Personalized and Explainable POI Recommender System

no code implementations20 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.)

Explainable Recommendation Recommendation Systems

Music Sequence Prediction with Mixture Hidden Markov Models

no code implementations27 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.

Collaborative Filtering Music Recommendation +1

Weakly Supervised Video Summarization by Hierarchical Reinforcement Learning

no code implementations12 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

Rethinking Motion Representation: Residual Frames with 3D ConvNets for Better Action Recognition

3 code implementations16 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.

Action Recognition Optical Flow Estimation

Motion Representation Using Residual Frames with 3D CNN

3 code implementations21 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.

Action Recognition Optical Flow Estimation

Self-supervised Video Representation Learning Using Inter-intra Contrastive Framework

2 code implementations6 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.

Action Recognition In Videos Contrastive Learning +6

Pretext-Contrastive Learning: Toward Good Practices in Self-supervised Video Representation Leaning

1 code implementation29 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.

Contrastive Learning Data Augmentation +4

Significant Ties Graph Neural Networks for Continuous-Time Temporal Networks Modeling

no code implementations12 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.

Epidemiology Recommendation Systems

Three-way causal attribute partial order structure analysis

no code implementations29 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.

Attribute

Transforming Graphs for Enhanced Attribute Clustering: An Innovative Graph Transformer-Based Method

no code implementations20 Jun 2023 Shuo Han, Jiacheng Liu, Jiayun Wu, Yinan Chen, Li Tao

The architecture of GTAGC encompasses graph embedding, integration of the Graph Transformer within the autoencoder structure, and a clustering component.

Attribute Clustering +5

Aligning Language Models with Offline Learning from Human Feedback

1 code implementation23 Aug 2023 Jian Hu, Li Tao, June Yang, Chandler Zhou

Learning from human preferences is crucial for language models (LMs) to effectively cater to human needs and societal values.

reinforcement-learning Reinforcement Learning (RL)

Resfusion: Prior Residual Noise embedded Denoising Diffusion Probabilistic Models

no code implementations25 Nov 2023 Shi Zhenning, Dong Changsheng, Pan Bin, Xie Xueshuo, He Along, Qu Qiaoying, Li Tao

Therefore, we propose Resfusion with a novel resnoise-diffusion process, which gradually generates segmentation masks or any type of target image, seamlessly integrating state-of-the-art end-to-end models and denoising diffusion models.

Denoising Image Generation +3

ResEnsemble-DDPM: Residual Denoising Diffusion Probabilistic Models for Ensemble Learning

no code implementations4 Dec 2023 Shi Zhenning, Dong Changsheng, Xie Xueshuo, Pan Bin, He Along, Li Tao

Rather than using denoising diffusion probabilistic models alone, integrating the abilities of both denoising diffusion probabilistic models and existing end-to-end models can better improve the performance of image segmentation.

Denoising Ensemble Learning +4

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