Search Results for author: Yu Xiong

Found 17 papers, 8 papers with code

XRL-Bench: A Benchmark for Evaluating and Comparing Explainable Reinforcement Learning Techniques

no code implementations20 Feb 2024 Yu Xiong, Zhipeng Hu, Ye Huang, Runze Wu, Kai Guan, Xingchen Fang, Ji Jiang, Tianze Zhou, Yujing Hu, Haoyu Liu, Tangjie Lyu, Changjie Fan

To address this, we introduce XRL-Bench, a unified standardized benchmark tailored for the evaluation and comparison of XRL methods, encompassing three main modules: standard RL environments, explainers based on state importance, and standard evaluators.

Decision Making Reinforcement Learning (RL)

Sequential Model for Predicting Patient Adherence in Subcutaneous Immunotherapy for Allergic Rhinitis

1 code implementation21 Jan 2024 Yin Li, Yu Xiong, Wenxin Fan, Kai Wang, Qingqing Yu, Liping Si, Patrick van der Smagt, Jun Tang, Nutan Chen

Conclusion: We creatively apply sequential models in the long-term management of SCIT with promising accuracy in the prediction of SCIT nonadherence in Allergic Rhinitis (AR) patients.

Management

PAD: Self-Supervised Pre-Training with Patchwise-Scale Adapter for Infrared Images

1 code implementation13 Dec 2023 Tao Zhang, Kun Ding, Jinyong Wen, Yu Xiong, Zeyu Zhang, Shiming Xiang, Chunhong Pan

Self-supervised learning (SSL) for RGB images has achieved significant success, yet there is still limited research on SSL for infrared images, primarily due to three prominent challenges: 1) the lack of a suitable large-scale infrared pre-training dataset, 2) the distinctiveness of non-iconic infrared images rendering common pre-training tasks like masked image modeling (MIM) less effective, and 3) the scarcity of fine-grained textures making it particularly challenging to learn general image features.

Self-Supervised Learning

Rethink Baseline of Integrated Gradients from the Perspective of Shapley Value

no code implementations7 Oct 2023 Shuyang Liu, Zixuan Chen, Ge Shi, Ji Wang, Changjie Fan, Yu Xiong, Runze Wu Yujing Hu, Ze Ji, Yang Gao

Thus, we propose a novel baseline construction method called Shapley Integrated Gradients (SIG) that searches for a set of baselines by proportional sampling to partly simulate the computation path of Shapley Value.

A Model-Agnostic Framework for Recommendation via Interest-aware Item Embeddings

no code implementations17 Aug 2023 Amit Kumar Jaiswal, Yu Xiong

However, these methods lack a modelling mechanism to directly reflect user interests within the learned item representations.

Recommendation Systems Representation Learning +1

Adaptive Value Decomposition with Greedy Marginal Contribution Computation for Cooperative Multi-Agent Reinforcement Learning

1 code implementation14 Feb 2023 Shanqi Liu, Yujing Hu, Runze Wu, Dong Xing, Yu Xiong, Changjie Fan, Kun Kuang, Yong liu

We first illustrate that the proposed value decomposition can consider the complicated interactions among agents and is feasible to learn in large-scale scenarios.

Multi-agent Reinforcement Learning

TCFimt: Temporal Counterfactual Forecasting from Individual Multiple Treatment Perspective

no code implementations17 Dec 2022 Pengfei Xi, Guifeng Wang, Zhipeng Hu, Yu Xiong, Mingming Gong, Wei Huang, Runze Wu, Yu Ding, Tangjie Lv, Changjie Fan, Xiangnan Feng

TCFimt constructs adversarial tasks in a seq2seq framework to alleviate selection and time-varying bias and designs a contrastive learning-based block to decouple a mixed treatment effect into separated main treatment effects and causal interactions which further improves estimation accuracy.

Contrastive Learning counterfactual +3

Transcript to Video: Efficient Clip Sequencing from Texts

no code implementations25 Jul 2021 Yu Xiong, Fabian Caba Heilbron, Dahua Lin

To meet the demands for non-experts, we present Transcript-to-Video -- a weakly-supervised framework that uses texts as input to automatically create video sequences from an extensive collection of shots.

Retrieval

MovieNet: A Holistic Dataset for Movie Understanding

no code implementations ECCV 2020 Qingqiu Huang, Yu Xiong, Anyi Rao, Jiaze Wang, Dahua Lin

We believe that such a holistic dataset would promote the researches on story-based long video understanding and beyond.

Video Understanding

A Local-to-Global Approach to Multi-modal Movie Scene Segmentation

4 code implementations CVPR 2020 Anyi Rao, Linning Xu, Yu Xiong, Guodong Xu, Qingqiu Huang, Bolei Zhou, Dahua Lin

Scene, as the crucial unit of storytelling in movies, contains complex activities of actors and their interactions in a physical environment.

Action Recognition Scene Segmentation +1

A Graph-Based Framework to Bridge Movies and Synopses

no code implementations ICCV 2019 Yu Xiong, Qingqiu Huang, Lingfeng Guo, Hang Zhou, Bolei Zhou, Dahua Lin

On top of this dataset, we develop a framework to perform matching between movie segments and synopsis paragraphs.

Hybrid Task Cascade for Instance Segmentation

5 code implementations CVPR 2019 Kai Chen, Jiangmiao Pang, Jiaqi Wang, Yu Xiong, Xiaoxiao Li, Shuyang Sun, Wansen Feng, Ziwei Liu, Jianping Shi, Wanli Ouyang, Chen Change Loy, Dahua Lin

In exploring a more effective approach, we find that the key to a successful instance segmentation cascade is to fully leverage the reciprocal relationship between detection and segmentation.

Instance Segmentation object-detection +5

Find and Focus: Retrieve and Localize Video Events with Natural Language Queries

no code implementations ECCV 2018 Dian Shao, Yu Xiong, Yue Zhao, Qingqiu Huang, Yu Qiao, Dahua Lin

The thriving of video sharing services brings new challenges to video retrieval, e. g. the rapid growth in video duration and content diversity.

Natural Language Queries Retrieval +2

From Trailers to Storylines: An Efficient Way to Learn from Movies

1 code implementation14 Jun 2018 Qingqiu Huang, Yuanjun Xiong, Yu Xiong, Yuqi Zhang, Dahua Lin

Experiments on this dataset showed that the proposed method can substantially reduce the training time while obtaining highly effective features and coherent temporal structures.

Unifying Identification and Context Learning for Person Recognition

1 code implementation CVPR 2018 Qingqiu Huang, Yu Xiong, Dahua Lin

In this work, we aim to move beyond such limitations and propose a new framework to leverage context for person recognition.

Face Recognition Person Recognition

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