no code implementations • 4 May 2024 • Xin Gao, Xin Yang, Hao Yu, Yan Kang, Tianrui Li
Federated Class-Incremental Learning (FCIL) focuses on continually transferring the previous knowledge to learn new classes in dynamic Federated Learning (FL).
no code implementations • 8 Apr 2024 • Shuai Guo, Jielei Chu, Lei Zhu, Zhaoyu Li, Tianrui Li
This paper introduces a novel variant of GFNs, the Dynamic Backtracking GFN (DB-GFN), which improves the adaptability of decision-making steps through a reward-based dynamic backtracking mechanism.
no code implementations • 1 Apr 2024 • Li Yang, Zhipeng Luo, Shiming Zhang, Fei Teng, Tianrui Li
We believe this survey can help relevant researchers quickly familiarize themselves with the current state of continual learning research used in smart city development and direct them to future research trends.
1 code implementation • 15 Mar 2024 • Xuemei Cao, Xin Yang, Shuyin Xia, Guoyin Wang, Tianrui Li
To this end, the proposed CFS method combines the strengths of continual learning (CL) with granular-ball computing (GBC), which focuses on constructing a granular-ball knowledge base to detect unknown classes and facilitate the transfer of previously learned knowledge for further feature selection.
1 code implementation • 14 Mar 2024 • Zhixuan Shen, Haonan Luo, Sijia Li, Tianrui Li
Scene-Text Visual Question Answering (ST-VQA) aims to understand scene text in images and answer questions related to the text content.
Optical Character Recognition Optical Character Recognition (OCR) +2
no code implementations • 12 Mar 2024 • Shipeng Song, Bin Liu, Fei Teng, Tianrui Li
Contrastive learning-based recommendation algorithms have significantly advanced the field of self-supervised recommendation, particularly with BPR as a representative ranking prediction task that dominates implicit collaborative filtering.
no code implementations • 1 Mar 2024 • Shiming Zhang, Zhipeng Luo, Li Yang, Fei Teng, Tianrui Li
Our survey offers a comprehensive review of route recommendation work based on urban computing.
2 code implementations • 29 Feb 2024 • Xingchen Zou, Yibo Yan, Xixuan Hao, Yuehong Hu, Haomin Wen, Erdong Liu, Junbo Zhang, Yong Li, Tianrui Li, Yu Zheng, Yuxuan Liang
As cities continue to burgeon, Urban Computing emerges as a pivotal discipline for sustainable development by harnessing the power of cross-domain data fusion from diverse sources (e. g., geographical, traffic, social media, and environmental data) and modalities (e. g., spatio-temporal, visual, and textual modalities).
1 code implementation • 9 Feb 2024 • Ziqiao Shang, Bin Liu, Fei Teng, Tianrui Li
To address the challenge posed by noisy AU labels, we augment the supervised signal through the introduction of a self-supervised signal.
no code implementations • 25 Jan 2024 • Chaofan Pan, Xin Yang, Hao Wang, Wei Wei, Tianrui Li
Despite the progress in continual reinforcement learning (CRL), existing methods often suffer from insufficient knowledge transfer, particularly when the tasks are diverse.
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 • 27 Dec 2023 • Xin Yang, Hao Yu, Xin Gao, Hao Wang, Junbo Zhang, Tianrui Li
The key objective of FCL is to fuse heterogeneous knowledge from different clients and retain knowledge of previous tasks while learning on new ones.
no code implementations • 27 Dec 2023 • Minbo Ma, Jilin Hu, Christian S. Jensen, Fei Teng, Peng Han, Zhiqiang Xu, Tianrui Li
Spatio-temporal forecasting of future values of spatially correlated time series is important across many cyber-physical systems (CPS).
no code implementations • 22 Dec 2023 • Yujie Li, Xin Yang, Hao Wang, Xiangkun Wang, Tianrui Li
This paper studies the problem of continual learning in an open-world scenario, referred to as Open-world Continual Learning (OwCL).
no code implementations • 31 Jul 2023 • Xinyao Liu, Shengdong Du, Fengmao Lv, Hongtao Xue, Jie Hu, Tianrui Li
In the era of big data, the issue of data quality has become increasingly prominent.
no code implementations • 22 May 2023 • Yuxia Chen, Pengcheng Fang, Jianhui Yu, Xiaoling Zhong, XiaoMing Zhang, Tianrui Li
In this work, we solve the above-mentioned problems by proposing a High-resolution remote sensing network (Hi-ResNet) with efficient network structure designs, which consists of a funnel module, a multi-branch module with stacks of information aggregation (IA) blocks, and a feature refinement module, sequentially, and Class-agnostic Edge Aware (CEA) loss.
Ranked #7 on Semantic Segmentation on LoveDA
no code implementations • 20 Mar 2023 • Yongyi Su, Xun Xu, Tianrui Li, Kui Jia
Test-time training (TTT) emerges as a solution to this adaptation under a realistic scenario where access to full source domain data is not available, and instant inference on the target domain is required.
1 code implementation • 27 Jan 2023 • Bin Liu, Bang Wang, Tianrui Li
Recent years have witnessed many successful applications of contrastive learning in diverse domains, yet its self-supervised version still remains many exciting challenges.
1 code implementation • ICCV 2023 • XiaoMing Zhang, Tianrui Li, Xiaole Zhao
Specifically, it is inspired by the temporal shifting in video understanding and displaces part of the channels along the spatial dimensions, thus allowing the effective receptive field to be amplified and the feature diversity to be augmented at almost zero cost.
1 code implementation • 27 Nov 2022 • Huaishao Luo, Junwei Bao, Youzheng Wu, Xiaodong He, Tianrui Li
The pre-trained model can capture enriched visual concepts for images by learning from a large scale of text-image data.
Ranked #1 on Semantic Segmentation on PASCAL VOC
no code implementations • 29 Aug 2022 • Xinyao Liu, Shengdong Du, Tianrui Li, Fei Teng, Yan Yang
We first incorporate into an autoencoder a hidden layer that consists of de-tracking neurons and radial basis function neurons, which can enhance the ability of learning interrelated features and common features.
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 • 11 Jun 2022 • Benhan Li, Shengdong Du, Tianrui Li, Jie Hu, Zhen Jia
Time-series forecasting plays an important role in many real-world scenarios, such as equipment life cycle forecasting, weather forecasting, and traffic flow forecasting.
no code implementations • 6 Apr 2022 • Peng Xie, Minbo Ma, Tianrui Li, Shenggong Ji, Shengdong Du, Zeng Yu, Junbo Zhang
Second, we employ a dynamic graph relationship learning module to learn dynamic spatial relationships between metro stations without a predefined graph adjacency matrix.
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 • 25 Feb 2022 • Jiabin Tang, Tang Qian, Shijing Liu, Shengdong Du, Jie Hu, Tianrui Li
Accurate traffic forecasting, the foundation of intelligent transportation systems (ITS), has never been more significant than nowadays due to the prosperity of smart cities and urban computing.
no code implementations • 23 Feb 2022 • Benhan Li, Shengdong Du, Tianrui Li
Time series forecasting is widely used in the fields of equipment life cycle forecasting, weather forecasting, traffic flow forecasting, and other fields.
no code implementations • 22 Jan 2022 • Minbo Ma, Peng Xie, Fei Teng, Tianrui Li, Bin Wang, Shenggong Ji, Junbo Zhang
In this paper, we propose a novel Hierarchical Spatio-Temporal Graph Neural Network (HiSTGNN) to model cross-regional spatio-temporal correlations among meteorological variables in multiple stations.
no code implementations • CVPR 2022 • Tao Liang, Guosheng Lin, Mingyang Wan, Tianrui Li, Guojun Ma, Fengmao Lv
Through the proposed MI2P unit, we can inject the language information into the vision backbone by attending the word-wise textual features to different visual channels, as well as inject the visual information into the language backbone by attending the channel-wise visual features to different textual words.
no code implementations • 14 Dec 2021 • Weiyi Li, Hongmei Chen, Tianrui Li, Jihong Wan, Binbin Sang
In this study, an unsupervised feature selection is proposed by integrating the framework of self-paced learning and subspace learning.
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.
5 code implementations • 18 Apr 2021 • Huaishao Luo, Lei Ji, Ming Zhong, Yang Chen, Wen Lei, Nan Duan, Tianrui Li
In this paper, we propose a CLIP4Clip model to transfer the knowledge of the CLIP model to video-language retrieval in an end-to-end manner.
Ranked #1 on Text to Video Retrieval on MSR-VTT
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.
no code implementations • 18 Dec 2020 • Wei Huang, Tianrui Li, Dexian Wang, Shengdong Du, Junbo Zhang
An appropriate weight selection algorithm that combines the information quantity of training accuracy and training frequency to measure the weights is proposed.
no code implementations • COLING 2020 • Hao Wang, Shuai Wang, Sahisnu Mazumder, Bing Liu, Yan Yang, Tianrui Li
After each sentiment classification task is learned, its knowledge is retained to help future task learning.
no code implementations • Asian Chapter of the Association for Computational Linguistics 2020 • Huaishao Luo, Yu Shi, Ming Gong, Linjun Shou, Tianrui Li
In this paper, we propose a novel approach that extends the probability vector to a probability matrix.
1 code implementation • Findings of the Association for Computational Linguistics 2020 • Huaishao Luo, Lei Ji, Tianrui Li, Nan Duan, Daxin Jiang
Specifically, a cascaded labeling module is developed to enhance the interchange between aspect terms and improve the attention of sentiment tokens when labeling sentiment polarities.
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +4
1 code implementation • 4 May 2020 • Ping Cai, Xingyuan Chen, Peng Jin, Hongjun Wang, Tianrui Li
The purpose of unconditional text generation is to train a model with real sentences, then generate novel sentences of the same quality and diversity as the training data.
no code implementations • 13 Mar 2020 • Jielei Chu, Jing Liu, Hongjun Wang, Meng Hua, Zhiguo Gong, Tianrui Li
To explore the representation learning capability under the continuous stimulation of the SPI, we present a deep Micro-supervised Disturbance Learning (Micro-DL) framework based on the Micro-DGRBM and Micro-DRBM models and compare it with a similar deep structure which has not any external stimulation.
2 code implementations • 15 Feb 2020 • Huaishao Luo, Lei Ji, Botian Shi, Haoyang Huang, Nan Duan, Tianrui Li, Jason Li, Taroon Bharti, Ming Zhou
However, most of the existing multimodal models are pre-trained for understanding tasks, leading to a pretrain-finetune discrepancy for generation tasks.
Ranked #2 on Action Segmentation on COIN (using extra training data)
no code implementations • IJCNLP 2019 • Hao Wang, Bing Liu, Chaozhuo Li, Yan Yang, Tianrui Li
We propose a novel DNN model called NetAb (as shorthand for convolutional neural Networks with Ab-networks) to handle noisy labels during training.
no code implementations • 26 Aug 2019 • Peng Xie, Tianrui Li, Jia Liu, Shengdong Du, Xin Yang, Junbo Zhang
Urban spatial-temporal flows prediction is of great importance to traffic management, land use, public safety, etc.
no code implementations • 12 Jun 2019 • Jielei Chu, Hongjun Wang, Jing Liu, Zhiguo Gong, Tianrui Li
In mcrRBM and mcrGRBM models, the structure and multi-local collaborative relationships of unlabeled data are integrated into their encoding procedure.
1 code implementation • ACL 2019 • Huaishao Luo, Tianrui Li, Bing Liu, Junbo Zhang
This paper focuses on two related subtasks of aspect-based sentiment analysis, namely aspect term extraction and aspect sentiment classification, which we call aspect term-polarity co-extraction.
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +3
3 code implementations • 22 Dec 2018 • Bin Wang, Jie Lu, Zheng Yan, Huaishao Luo, Tianrui Li, Yu Zheng, Guangquan Zhang
We cast the weather forecasting problem as an end-to-end deep learning problem and solve it by proposing a novel negative log-likelihood error (NLE) loss function.
no code implementations • 12 Dec 2018 • Shengdong Du, Tianrui Li, Yan Yang, Shi-Jinn Horng
Air quality forecasting has been regarded as the key problem of air pollution early warning and control management.
no code implementations • 5 Dec 2018 • Jielei Chu, Hongjun Wang, Jing Liu, Zhiguo Gong, Tianrui Li
In this paper, we present a novel unsupervised feature learning architecture, which consists of a multi-clustering integration module and a variant of RBM termed multi-clustering integration RBM (MIRBM).
1 code implementation • 21 May 2018 • Huaishao Luo, Tianrui Li, Bing Liu, Bin Wang, Herwig Unger
The key idea is to explicitly incorporate both representations gained separately from the bottom-up and top-down propagation on the given dependency syntactic tree.
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +1
no code implementations • 6 Mar 2018 • Shengdong Du, Tianrui Li, Xun Gong, Shi-Jinn Horng
Traffic flow forecasting has been regarded as a key problem of intelligent transport systems.
no code implementations • 22 Nov 2017 • Zeng Yu, Tianrui Li, Ning Yu, Xun Gong, Ke Chen, Yi Pan
This paper aims to develop a new architecture that can make full use of the feature maps of convolutional networks.
no code implementations • 8 Oct 2017 • Zeng Yu, Tianrui Li, Ning Yu, Yi Pan, Hongmei Chen, Bing Liu
We believe that minimizing the reconstruction error of the hidden representation is more robust than minimizing the Frobenius norm of the Jacobian matrix of the hidden representation.
no code implementations • 13 Jan 2017 • Jielei Chu, Hongjun Wang, Hua Meng, Peng Jin, Tianrui Li
To enhance the expression ability of traditional RBMs, in this paper, we propose pairwise constraints restricted Boltzmann machine with Gaussian visible units (pcGRBM) model, in which the learning procedure is guided by pairwise constraints and the process of encoding is conducted under these guidances.
no code implementations • 10 Jan 2017 • Junbo Zhang, Yu Zheng, Dekang Qi, Ruiyuan Li, Xiuwen Yi, Tianrui Li
We propose a deep-learning-based approach, called ST-ResNet, to collectively forecast two types of crowd flows (i. e. inflow and outflow) in each and every region of a city.
no code implementations • 6 Oct 2016 • Junbo Zhang, Tianrui Li, Yi Pan
The rapid growth of emerging information technologies and application patterns in modern society, e. g., Internet, Internet of Things, Cloud Computing and Tri-network Convergence, has caused the advent of the era of big data.
no code implementations • IJCAI 2016 2016 • Xiuwen Yi, Yu Zheng, Junbo Zhang, Tianrui Li
In this paper, we propose a spatio-temporal multi-view-based learning (ST-MVL) method to collectively fill missing readings in a collection of geosensory time series data, considering 1) the temporal correlation between readings at different timestamps in the same series and 2) the spatial correlation between different time series.
Collaborative Filtering Multivariate Time Series Imputation +3