no code implementations • 7 May 2024 • Hao Wu, Ruochong LI, Hao Wang, Hui Xiong
To address this issue, we propose COM3D, making the first attempt to exploit the cross-view correspondence and cross-modal mining to enhance the retrieval performance.
no code implementations • 23 Apr 2024 • Chao Chen, Chenghua Guo, Rui Xu, Xiangwen Liao, Xi Zhang, Sihong Xie, Hui Xiong, Philip Yu
Graphical models, including Graph Neural Networks (GNNs) and Probabilistic Graphical Models (PGMs), have demonstrated their exceptional capabilities across numerous fields.
1 code implementation • 19 Apr 2024 • Tianfu Wang, Qilin Fan, Chao Wang, Long Yang, Leilei Ding, Nicholas Jing Yuan, Hui Xiong
In this paper, we propose a FLexible And Generalizable RL framework for VNE, named FlagVNE.
no code implementations • 17 Apr 2024 • Weiyu Guo, Ziyue Qiao, Ying Sun, Hui Xiong
We propose a Short Term Enhancement Module(STEM) which can be easily integrated with various models.
1 code implementation • 16 Apr 2024 • Jianqi Zhang, Jingyao Wang, Wenwen Qiang, Fanjiang Xu, Changwen Zheng, Fuchun Sun, Hui Xiong
Motivated by these findings, we introduce two new PEs: Temporal Position Encoding (T-PE) for temporal tokens and Variable Positional Encoding (V-PE) for variable tokens.
no code implementations • 13 Apr 2024 • Feihu Jiang, Chuan Qin, Jingshuai Zhang, Kaichun Yao, Xi Chen, Dazhong Shen, Chen Zhu, HengShu Zhu, Hui Xiong
In the contemporary era of widespread online recruitment, resume understanding has been widely acknowledged as a fundamental and crucial task, which aims to extract structured information from resume documents automatically.
no code implementations • 10 Apr 2024 • Feihu Jiang, Chuan Qin, Kaichun Yao, Chuyu Fang, Fuzhen Zhuang, HengShu Zhu, Hui Xiong
For the generation process, we propose a novel chain of thought (CoT) based fine-tuning method to empower the LLM-based generator to adeptly respond to user questions using retrieved documents.
no code implementations • 5 Apr 2024 • Zhihao Guan, Jia-Qi Yang, Yang Yang, HengShu Zhu, Wenjie Li, Hui Xiong
Moreover, we adopt a two-stage learning strategy for skill-aware recommendation, in which we utilize the skill distribution to guide JD representation learning in the recall stage, and then combine the user profiles for final prediction in the ranking stage.
1 code implementation • 3 Apr 2024 • Yunfan Lu, Yijie Xu, Wenzong Ma, Weiyu Guo, Hui Xiong
To end this, we present a Swin-Transformer-based backbone and a pixel-focus loss function for demosaicing with missing pixel values in RAW domain processing.
1 code implementation • 26 Mar 2024 • Wei Wu, Chao Wang, Dazhong Shen, Chuan Qin, Liyi Chen, Hui Xiong
Collaborative filtering methods based on graph neural networks (GNNs) have witnessed significant success in recommender systems (RS), capitalizing on their ability to capture collaborative signals within intricate user-item relationships via message-passing mechanisms.
no code implementations • 20 Mar 2024 • Zhi Zheng, Wenshuo Chao, Zhaopeng Qiu, HengShu Zhu, Hui Xiong
Recent advances in Large Language Models (LLMs) have been changing the paradigm of Recommender Systems (RS).
2 code implementations • 4 Mar 2024 • Yiqian Yang, Yiqun Duan, Qiang Zhang, Renjing Xu, Hui Xiong
In this paper, we explore the brain-to-text translation of MEG signals in a speech-decoding formation.
1 code implementation • 21 Feb 2024 • Siyang Li, Hui Xiong, Yize Chen
Accordingly, we devise a novel Diffusion model termed DiffPLF for Probabilistic Load Forecasting of EV charging, which can explicitly approximate the predictive load distribution conditioned on historical data and related covariates.
no code implementations • 5 Feb 2024 • Shuyao Wang, Yongduo Sui, Jiancan Wu, Zhi Zheng, Hui Xiong
In the realm of deep learning-based recommendation systems, the increasing computational demands, driven by the growing number of users and items, pose a significant challenge to practical deployment.
1 code implementation • 30 Jan 2024 • Weijia Zhang, Jindong Han, Zhao Xu, Hang Ni, Hao liu, Hui Xiong
Machine learning techniques are now integral to the advancement of intelligent urban services, playing a crucial role in elevating the efficiency, sustainability, and livability of urban environments.
no code implementations • 29 Jan 2024 • Wei Ju, Yiyang Gu, Zhengyang Mao, Ziyue Qiao, Yifang Qin, Xiao Luo, Hui Xiong, Ming Zhang
Self-supervised graph representation learning has recently shown considerable promise in a range of fields, including bioinformatics and social networks.
1 code implementation • 25 Jan 2024 • Jiangmeng Li, Fei Song, Yifan Jin, Wenwen Qiang, Changwen Zheng, Fuchun Sun, Hui Xiong
From the perspective of distribution analyses, we disclose that the intrinsic issues behind the phenomenon are the over-multitudinous conceptual knowledge contained in PLMs and the abridged knowledge for target downstream domains, which jointly result in that PLMs mis-locate the knowledge distributions corresponding to the target domains in the universal knowledge embedding space.
no code implementations • 22 Jan 2024 • Jinliang Deng, Xuan Song, Ivor W. Tsang, Hui Xiong
Through this work, we advocate a paradigm shift in LTSF, emphasizing the importance to tailor the model to the inherent dynamics of time series data-a timely reminder that in the realm of LTSF, bigger is not invariably better.
1 code implementation • 26 Dec 2023 • Siqi Lai, Zhao Xu, Weijia Zhang, Hao liu, Hui Xiong
Traffic Signal Control (TSC) is a crucial component in urban traffic management, aiming to optimize road network efficiency and reduce congestion.
no code implementations • 25 Dec 2023 • TianHui Ma, Yuan Cheng, HengShu Zhu, Hui Xiong
With the significant successes of large language models (LLMs) in many natural language processing tasks, there is growing interest among researchers in exploring LLMs for novel recommender systems.
1 code implementation • 19 Dec 2023 • Wenzhao Jiang, Hao liu, Hui Xiong
Moreover, we introduce a taxonomy of Causality-Inspired GNNs (CIGNNs) based on the type of causal learning capability they are equipped with, i. e., causal reasoning and causal representation learning.
1 code implementation • 17 Dec 2023 • Jiankai Sun, Chuanyang Zheng, Enze Xie, Zhengying Liu, Ruihang Chu, Jianing Qiu, Jiaqi Xu, Mingyu Ding, Hongyang Li, Mengzhe Geng, Yue Wu, Wenhai Wang, Junsong Chen, Zhangyue Yin, Xiaozhe Ren, Jie Fu, Junxian He, Wu Yuan, Qi Liu, Xihui Liu, Yu Li, Hao Dong, Yu Cheng, Ming Zhang, Pheng Ann Heng, Jifeng Dai, Ping Luo, Jingdong Wang, Ji-Rong Wen, Xipeng Qiu, Yike Guo, Hui Xiong, Qun Liu, Zhenguo Li
Reasoning, a crucial ability for complex problem-solving, plays a pivotal role in various real-world settings such as negotiation, medical diagnosis, and criminal investigation.
no code implementations • 13 Dec 2023 • Aiwei Liu, Leyi Pan, Yijian Lu, Jingjing Li, Xuming Hu, Xi Zhang, Lijie Wen, Irwin King, Hui Xiong, Philip S. Yu
Text watermarking algorithms play a crucial role in the copyright protection of textual content, yet their capabilities and application scenarios have been limited historically.
1 code implementation • 4 Dec 2023 • Zhengyu Hu, Jieyu Zhang, Yue Yu, Yuchen Zhuang, Hui Xiong
This paper presents LEMR (Label-Efficient Model Ranking) and introduces the MoraBench Benchmark.
no code implementations • 29 Nov 2023 • Jinhui Ye, Jiaming Zhou, Hui Xiong, Junwei Liang
Specifically, at the core of GeoDeformer is the Geometric Deformation Predictor, a module designed to identify and quantify potential spatial and temporal geometric deformations within the given video.
1 code implementation • 15 Nov 2023 • Yunqin Zhu, Chao Wang, Qi Zhang, Hui Xiong
In this paper, we adapt standard diffusion model and propose a novel Graph Signal Diffusion Model for Collaborative Filtering (named GiffCF).
no code implementations • 13 Nov 2023 • Kaichen Zhang, Ohchan Kwon, Hui Xiong
The rise of generative artificial intelligence (AI) has sparked concerns about its potential influence on unemployment and market depression.
no code implementations • 10 Nov 2023 • Hangtong Xu, Yuanbo Xu, Yongjian Yang, Fuzhen Zhuang, Hui Xiong
We demonstrate theoretically that our approach mitigates the negative effects of feedback loops and unknown exposure mechanisms.
1 code implementation • 23 Oct 2023 • Yihuai Lan, Zhiqiang Hu, Lei Wang, Yang Wang, Deheng Ye, Peilin Zhao, Ee-Peng Lim, Hui Xiong, Hao Wang
To achieve this goal, we adopt Avalon, a representative communication game, as the environment and use system prompts to guide LLM agents to play the game.
1 code implementation • 21 Oct 2023 • Chuang Zhao, Hongke Zhao, HengShu Zhu, Zhenya Huang, Nan Feng, Enhong Chen, Hui Xiong
One prevalent solution is the bi-discriminator domain adversarial network, which strives to identify target domain samples outside the support of the source domain distribution and enforces their classification to be consistent on both discriminators.
5 code implementations • 16 Oct 2023 • Ming Jin, Qingsong Wen, Yuxuan Liang, Chaoli Zhang, Siqiao Xue, Xue Wang, James Zhang, Yi Wang, Haifeng Chen, XiaoLi Li, Shirui Pan, Vincent S. Tseng, Yu Zheng, Lei Chen, Hui Xiong
In this survey, we offer a comprehensive and up-to-date review of large models tailored (or adapted) for time series and spatio-temporal data, spanning four key facets: data types, model categories, model scopes, and application areas/tasks.
no code implementations • 14 Oct 2023 • Jindong Han, Weijia Zhang, Hao liu, Hui Xiong
In this article, we present a comprehensive survey of ML-based air quality analytics, following a roadmap spanning from data acquisition to pre-processing, and encompassing various analytical tasks such as pollution pattern mining, air quality inference, and forecasting.
no code implementations • ICCV 2023 • Lu Dai, Liqian Ma, Shenhan Qian, Hao liu, Ziwei Liu, Hui Xiong
Finally, how to generate diverse and plausible results from a 2D clothing image.
no code implementations • 27 Sep 2023 • Ying Sun, HengShu Zhu, Hui Xiong
Self-interpreting neural networks have garnered significant interest in research.
no code implementations • 19 Sep 2023 • Ziyue Qiao, Xiao Luo, Meng Xiao, Hao Dong, Yuanchun Zhou, Hui Xiong
To deal with the domain shift, we add adaptive shift parameters to each of the source nodes, which are trained in an adversarial manner to align the cross-domain distributions of node embedding, thus the node classifier trained on labeled source nodes can be transferred to the target nodes.
no code implementations • 31 Aug 2023 • Weijia Zhang, Le Zhang, Jindong Han, Hao liu, Jingbo Zhou, Yu Mei, Hui Xiong
Accurate traffic forecasting at intersections governed by intelligent traffic signals is critical for the advancement of an effective intelligent traffic signal control system.
1 code implementation • 18 Aug 2023 • Siyang Li, Hui Xiong, Yize Chen
Recent proliferation of electric vehicle (EV) charging events has brought prominent stress over power grid operation.
no code implementations • 3 Aug 2023 • Hui Xiong, Congying Chu, Lingzhong Fan, Ming Song, JiaQi Zhang, Yawei Ma, Ruonan Zheng, Junyang Zhang, Zhengyi Yang, Tianzi Jiang
In recent years, advances in neuroscience and artificial intelligence have paved the way for unprecedented opportunities for understanding the complexity of the brain and its emulation by computational systems.
1 code implementation • 18 Jul 2023 • Jingyao Wang, Wenwen Qiang, Xingzhe Su, Changwen Zheng, Fuchun Sun, Hui Xiong
We obtain three conclusions: (i) there is no universal task sampling strategy that can guarantee the optimal performance of meta-learning models; (ii) over-constraining task diversity may incur the risk of under-fitting or over-fitting during training; and (iii) the generalization performance of meta-learning models are affected by task diversity, task entropy, and task difficulty.
1 code implementation • 14 Jul 2023 • Qi Liu, Zheng Gong, Zhenya Huang, Chuanren Liu, HengShu Zhu, Zhi Li, Enhong Chen, Hui Xiong
Machine learning algorithms have become ubiquitous in a number of applications (e. g. image classification).
no code implementations • 5 Jul 2023 • Zhi Zheng, Zhaopeng Qiu, Xiao Hu, Likang Wu, HengShu Zhu, Hui Xiong
The rapid development of online recruitment services has encouraged the utilization of recommender systems to streamline the job seeking process.
no code implementations • 3 Jul 2023 • Chuan Qin, Le Zhang, Yihang Cheng, Rui Zha, Dazhong Shen, Qi Zhang, Xi Chen, Ying Sun, Chen Zhu, HengShu Zhu, Hui Xiong
To this end, we present an up-to-date and comprehensive survey on AI technologies used for talent analytics in the field of human resource management.
no code implementations • 30 Jun 2023 • Qizhi Wan, Changxuan Wan, Keli Xiao, Hui Xiong, Dexi Liu, Xiping Liu
This paper introduces a novel framework for document-level event extraction, incorporating a new data structure called token-event-role and a multi-channel argument role prediction module.
1 code implementation • 29 Jun 2023 • Meng Xiao, Dongjie Wang, Min Wu, Kunpeng Liu, Hui Xiong, Yuanchun Zhou, Yanjie Fu
Feature transformation aims to reconstruct an effective representation space by mathematically refining the existing features.
1 code implementation • 21 Jun 2023 • Congxi Xiao, Jingbo Zhou, Jizhou Huang, Tong Xu, Hui Xiong
However, urban graphs usually can be observed to possess a unique spatial heterophily property; that is, the dissimilarity of neighbors at different spatial distances can exhibit great diversity.
1 code implementation • NeurIPS 2023 • Yansong Ning, Hao liu, Hao Wang, Zhenyu Zeng, Hui Xiong
We hope the proposed UUKG fosters research on urban knowledge graphs and broad smart city applications.
1 code implementation • 16 Jun 2023 • Wen-Zhi Li, Chang-Dong Wang, Hui Xiong, Jian-Huang Lai
Class imbalance is the phenomenon that some classes have much fewer instances than others, which is ubiquitous in real-world graph-structured scenarios.
1 code implementation • 16 Jun 2023 • Wen-Zhi Li, Chang-Dong Wang, Hui Xiong, Jian-Huang Lai
Contrastive learning (CL) has become the de-facto learning paradigm in self-supervised learning on graphs, which generally follows the "augmenting-contrasting" learning scheme.
1 code implementation • 15 Jun 2023 • Shuangli Li, Jingbo Zhou, Ji Liu, Tong Xu, Enhong Chen, Hui Xiong
Specifically, we propose a solution to Trial with a graph learning scheme, which includes a spatially evolving graph neural network (SEENet) with two collaborative components: spatially evolving graph convolution module (SEConv) and spatially evolving self-supervised learning strategy (SE-SSL).
no code implementations • 31 May 2023 • Xingzhe Su, Changwen Zheng, Wenwen Qiang, Fengge Wu, Junsuo Zhao, Fuchun Sun, Hui Xiong
This study identifies a previously overlooked issue: GANs exhibit a heightened susceptibility to overfitting on remote sensing images. To address this challenge, this paper analyzes the characteristics of remote sensing images and proposes manifold constraint regularization, a novel approach that tackles overfitting of GANs on remote sensing images for the first time.
1 code implementation • 31 May 2023 • Likang Wu, Zhi Zheng, Zhaopeng Qiu, Hao Wang, Hongchao Gu, Tingjia Shen, Chuan Qin, Chen Zhu, HengShu Zhu, Qi Liu, Hui Xiong, Enhong Chen
Large Language Models (LLMs) have emerged as powerful tools in the field of Natural Language Processing (NLP) and have recently gained significant attention in the domain of Recommendation Systems (RS).
no code implementations • 25 May 2023 • Yiqi Lin, Hao Wu, Ruichen Wang, Haonan Lu, Xiaodong Lin, Hui Xiong, Lin Wang
Generating and editing a 3D scene guided by natural language poses a challenge, primarily due to the complexity of specifying the positional relations and volumetric changes within the 3D space.
1 code implementation • 24 May 2023 • Yiheng Jiang, Yuanbo Xu, Yongjian Yang, Funing Yang, Pengyang Wang, Hui Xiong
In this paper, we present a MLP-like architecture for sequential recommendation, namely TriMLP, with a novel Triangular Mixer for cross-token communications.
1 code implementation • 18 May 2023 • Jinhui Ye, Wenxiang Jiao, Xing Wang, Zhaopeng Tu, Hui Xiong
It has been a challenging task due to the modality gap between sign videos and texts and the data scarcity of labeled data.
Ranked #3 on Sign Language Translation on CSL-Daily
1 code implementation • 18 May 2023 • Chenguang Du, Kaichun Yao, HengShu Zhu, Deqing Wang, Fuzhen Zhuang, Hui Xiong
However, existing HGNNs usually represent each node as a single vector in the multi-layer graph convolution calculation, which makes the high-level graph convolution layer fail to distinguish information from different relations and different orders, resulting in the information loss in the message passing.
no code implementations • 18 May 2023 • Chao Wang, HengShu Zhu, Dazhong Shen, Wei Wu, Hui Xiong
In this way, the low-rating items will be treated as positive samples for modeling intents while the negative samples for modeling preferences.
no code implementations • 4 Feb 2023 • Kun Yi, Qi Zhang, Longbing Cao, Shoujin Wang, Guodong Long, Liang Hu, Hui He, Zhendong Niu, Wei Fan, Hui Xiong
Despite the growing attention and the proliferation of research in this emerging field, there is currently a lack of a systematic review and in-depth analysis of deep learning-based time series models with FT.
1 code implementation • 5 Jan 2023 • Miao Chen, Xinjiang Lu, Tong Xu, Yanyan Li, Jingbo Zhou, Dejing Dou, Hui Xiong
Although remarkable progress on the neural table-to-text methods has been made, the generalization issues hinder the applicability of these models due to the limited source tables.
1 code implementation • 30 Dec 2022 • Chengyang Gu, Hui Xiong, Yize Chen
Solving real-world optimal control problems are challenging tasks, as the complex, high-dimensional system dynamics are usually unrevealed to the decision maker.
Model-based Reinforcement Learning Reinforcement Learning (RL)
no code implementations • 26 Nov 2022 • Congxi Xiao, Jingbo Zhou, Jizhou Huang, HengShu Zhu, Tong Xu, Dejing Dou, Hui Xiong
The core idea of such a framework is to firstly pre-train a basis (or master) model over the URG, and then to adaptively derive specific (or slave) models from the basis model for different regions.
no code implementations • 16 Sep 2022 • Meng Xiao, Ziyue Qiao, Yanjie Fu, Hao Dong, Yi Du, Pengyang Wang, Hui Xiong, Yuanchun Zhou
Specifically, we first propose a hierarchical transformer to extract the textual semantic information of proposals.
2 code implementations • 16 Sep 2022 • Jiangmeng Li, Wenwen Qiang, Yanan Zhang, Wenyi Mo, Changwen Zheng, Bing Su, Hui Xiong
As a successful approach to self-supervised learning, contrastive learning aims to learn invariant information shared among distortions of the input sample.
no code implementations • 16 Sep 2022 • Meng Xiao, Dongjie Wang, Min Wu, Kunpeng Liu, Hui Xiong, Yuanchun Zhou, Yanjie Fu
Feature transformation aims to extract a good representation (feature) space by mathematically transforming existing features.
2 code implementations • 16 Sep 2022 • Jiangmeng Li, Wenwen Qiang, Changwen Zheng, Bing Su, Farid Razzak, Ji-Rong Wen, Hui Xiong
To this end, we propose a methodology, specifically consistency and complementarity network (CoCoNet), which avails of strict global inter-view consistency and local cross-view complementarity preserving regularization to comprehensively learn representations from multiple views.
1 code implementation • ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2022 • Shengming Zhang, Yanchi Liu, Xuchao Zhang, Wei Cheng, Haifeng Chen, Hui Xiong
It is critical and important to detect anomalies in event sequences, which becomes widely available in many application domains. In-deed, various efforts have been made to capture abnormal patterns from event sequences through sequential pattern analysis or event representation learning. However, existing approaches usually ignore the semantic information of event content. To this end, in this paper, we propose a self-attentive encoder-decoder transformer framework, Content-Aware Transformer(CAT), for anomaly detection in event sequences. In CAT, the encoder learns preamble event sequence representations with content awareness, and the decoder embeds sequences under detection into a latent space, where anomalies are distinguishable. Specifically, the event content is first fed to a content-awareness layer, generating representations of each event. The encoder accepts preamble event representation sequence, generating feature maps. In the decoder, an additional token is added at the beginning of the sequence under detection, denoting the sequence status. A one-class objective together with sequence reconstruction loss is collectively applied to train our framework under the label efficiency scheme. Furthermore, CAT is optimized under a scalable and efficient setting. Finally, extensive experiments on three real-world datasets demonstrate the superiority of CAT.
1 code implementation • 30 Jun 2022 • Liangzhe Han, Xiaojian Ma, Leilei Sun, Bowen Du, Yanjie Fu, Weifeng Lv, Hui Xiong
Traffic demand forecasting by deep neural networks has attracted widespread interest in both academia and industry society.
no code implementations • 30 Jun 2022 • Shuokai Li, Yongchun Zhu, Ruobing Xie, Zhenwei Tang, Zhao Zhang, Fuzhen Zhuang, Qing He, Hui Xiong
In this paper, we propose two key points for CRS to improve the user experience: (1) Speaking like a human, human can speak with different styles according to the current dialogue context.
no code implementations • 29 Jun 2022 • Wenwen Qiang, Jiangmeng Li, Changwen Zheng, Bing Su, Hui Xiong
Contrastive learning (CL)-based self-supervised learning models learn visual representations in a pairwise manner.
1 code implementation • 28 Jun 2022 • Junchen Ye, Zihan Liu, Bowen Du, Leilei Sun, Weimiao Li, Yanjie Fu, Hui Xiong
To equip the graph neural network with a flexible and practical graph structure, in this paper, we investigate how to model the evolutionary and multi-scale interactions of time series.
1 code implementation • 4 Jun 2022 • Yunfan Lu, Yiqi Lin, Hao Wu, Yunhao Luo, Xu Zheng, Hui Xiong, Lin Wang
Image restoration and enhancement is a process of improving the image quality by removing degradations, such as noise, blur, and resolution degradation.
no code implementations • 19 May 2022 • Yuanbo Xu, Yongjian Yang, En Wang, Fuzhen Zhuang, Hui Xiong
2) the PMU detection model should take both ratings and reviews into consideration, which makes PMU detection a multi-modal problem.
no code implementations • 12 May 2022 • Wei Fan, Kunpeng Liu, Hao liu, HengShu Zhu, Hui Xiong, Yanjie Fu
Feature selection and instance selection are two important techniques of data processing.
no code implementations • 13 Mar 2022 • Dongjie Wang, Pengyang Wang, Yanjie Fu, Kunpeng Liu, Hui Xiong, Charles E. Hughes
The profiling framework is formulated into a reinforcement learning task, where an agent is a next-visit planner, an action is a POI that a user will visit next, and the state of the environment is a fused representation of a user and spatial entities.
2 code implementations • 10 Mar 2022 • Jiangmeng Li, Wenwen Qiang, Changwen Zheng, Bing Su, Hui Xiong
We perform a meta learning technique to build the augmentation generator that updates its network parameters by considering the performance of the encoder.
no code implementations • 8 Mar 2022 • Wenwen Qiang, Jiangmeng Li, Changwen Zheng, Bing Su, Hui Xiong
We conduct theoretical analysis on the robustness of the proposed RLPGA and prove that the robust informative-theoretic-based loss and the local preserving module are beneficial to reduce the empirical risk of the target domain.
1 code implementation • 28 Feb 2022 • Menglin Yang, Min Zhou, Zhihao LI, Jiahong Liu, Lujia Pan, Hui Xiong, Irwin King
Graph neural networks generalize conventional neural networks to graph-structured data and have received widespread attention due to their impressive representation ability.
no code implementations • 19 Jan 2022 • Dongjie Wang, Kunpeng Liu, Hui Xiong, Yanjie Fu
An event that a user visits a POI in stream updates the states of both users and geospatial contexts; the agent perceives the updated environment state to make online recommendations.
no code implementations • 31 Dec 2021 • Dongbo Xi, Fuzhen Zhuang, Yanchi Liu, Jingjing Gu, Hui Xiong, Qing He
Then, target temporal pattern in combination with user and POI information are fed into a multi-layer network to capture users' dynamic preferences.
1 code implementation • 23 Dec 2021 • Denghui Zhang, Zixuan Yuan, Hao liu, Xiaodong Lin, Hui Xiong
Graph walking based on reinforcement learning (RL) has shown great success in navigating an agent to automatically complete various reasoning tasks over an incomplete knowledge graph (KG) by exploring multi-hop relational paths.
no code implementations • 2 Dec 2021 • Zixuan Yuan, Yada Zhu, Wei zhang, Ziming Huang, Guangnan Ye, Hui Xiong
Earnings call (EC), as a periodic teleconference of a publicly-traded company, has been extensively studied as an essential market indicator because of its high analytical value in corporate fundamentals.
no code implementations • 1 Dec 2021 • Denghui Zhang, Zixuan Yuan, Yanchi Liu, Hao liu, Fuzhen Zhuang, Hui Xiong, Haifeng Chen
Also, the word co-occurrences guided semantic learning of pre-training models can be largely augmented by entity-level association knowledge.
1 code implementation • NeurIPS 2021 • Ying Sun, HengShu Zhu, Chuan Qin, Fuzhen Zhuang, Qing He, Hui Xiong
To this end, in this paper, we aim to discern the decision-making processes of neural networks through a hierarchical voting strategy by developing an explainable deep learning model, namely Voting Transformation-based Explainable Neural Network (VOTEN).
1 code implementation • NeurIPS 2021 • Dazhong Shen, Chuan Qin, Chao Wang, Zheng Dong, HengShu Zhu, Hui Xiong
To this end, in this paper, we revisit the task of topic modeling by transforming each document into a directed graph with word dependency as edges between word nodes, and develop a novel approach, namely Graph Neural Topic Model (GNTM).
no code implementations • 11 Nov 2021 • Zhao Zhang, Fuzhen Zhuang, HengShu Zhu, Chao Li, Hui Xiong, Qing He, Yongjun Xu
This will lead to low-quality and unreliable representations of KGs.
1 code implementation • 24 Oct 2021 • Dazhong Shen, Chuan Qin, Chao Wang, HengShu Zhu, Enhong Chen, Hui Xiong
As one of the most popular generative models, Variational Autoencoder (VAE) approximates the posterior of latent variables based on amortized variational inference.
no code implementations • 22 Oct 2021 • Yang Yang, Hongchen Wei, HengShu Zhu, dianhai yu, Hui Xiong, Jian Yang
In detail, considering that the heterogeneous gap between modalities always leads to the supervision difficulty of using the global embedding directly, CPRC turns to transform both the raw image and corresponding generated sentence into the shared semantic space, and measure the generated sentence from two aspects: 1) Prediction consistency.
no code implementations • 29 Sep 2021 • Wenwen Qiang, Jiangmeng Li, Jie Hu, Bing Su, Changwen Zheng, Hui Xiong
In this paper, we give an analysis of the existing representation learning framework of unsupervised domain adaptation and show that the learned feature representations of the source domain samples are with discriminability, compressibility, and transferability.
no code implementations • INFORMS Journal 2021 • Junming Liu, Weiwei Chen, Jingyuan Yang, Hui Xiong, Can Chen
Summary of Contribution: We propose an iterative prediction-and-optimization algorithm for multilevel distribution network design for e-logistics and evaluate its operational value for online retailers.
1 code implementation • 24 Sep 2021 • Shuangli Li, Jingbo Zhou, Tong Xu, Dejing Dou, Hui Xiong
Though graph contrastive learning (GCL) methods have achieved extraordinary performance with insufficient labeled data, most focused on designing data augmentation schemes for general graphs.
no code implementations • 24 Sep 2021 • Linlang Jiang, Jingbo Zhou, Tong Xu, Yanyan Li, Hao Chen, Jizhou Huang, Hui Xiong
To that end, we propose an Adversarial Neural Trip Recommendation (ANT) framework to tackle the above challenges.
no code implementations • 6 Sep 2021 • Jiangmeng Li, Wenwen Qiang, Hang Gao, Bing Su, Farid Razzak, Jie Hu, Changwen Zheng, Hui Xiong
To this end, we rethink the existing multi-view learning paradigm from the information theoretical perspective and then propose a novel information theoretical framework for generalized multi-view learning.
1 code implementation • 21 Jul 2021 • Shuangli Li, Jingbo Zhou, Tong Xu, Liang Huang, Fan Wang, Haoyi Xiong, Weili Huang, Dejing Dou, Hui Xiong
To this end, we propose a structure-aware interactive graph neural network (SIGN) which consists of two components: polar-inspired graph attention layers (PGAL) and pairwise interactive pooling (PiPool).
Ranked #3 on Protein-Ligand Affinity Prediction on PDBbind
no code implementations • 12 Jul 2021 • Weijia Zhang, Hao liu, Lijun Zha, HengShu Zhu, Ji Liu, Dejing Dou, Hui Xiong
Real estate appraisal refers to the process of developing an unbiased opinion for real property's market value, which plays a vital role in decision-making for various players in the marketplace (e. g., real estate agents, appraisers, lenders, and buyers).
1 code implementation • 17 Jun 2021 • Yongchun Zhu, Fuzhen Zhuang, Jindong Wang, Guolin Ke, Jingwu Chen, Jiang Bian, Hui Xiong, Qing He
The adaptation can be achieved easily with most feed-forward network models by extending them with LMMD loss, which can be trained efficiently via back-propagation.
1 code implementation • 14 Jun 2021 • Xiaoxiao Ma, Jia Wu, Shan Xue, Jian Yang, Chuan Zhou, Quan Z. Sheng, Hui Xiong, Leman Akoglu
In this survey, we aim to provide a systematic and comprehensive review of the contemporary deep learning techniques for graph anomaly detection.
1 code implementation • 24 May 2021 • Le Yu, Leilei Sun, Bowen Du, Chuanren Liu, Weifeng Lv, Hui Xiong
Moreover, a semantic fusing module is presented to aggregate relation-aware node representations into a compact representation with the learned relation representations.
Ranked #21 on Node Property Prediction on ogbn-mag
no code implementations • 24 Feb 2021 • Jinyin Chen, Xiang Lin, Dunjie Zhang, Wenrong Jiang, Guohan Huang, Hui Xiong, Yun Xiang
To the best of our knowledge, this is the first targeted label attack technique.
1 code implementation • 15 Feb 2021 • Weijia Zhang, Hao liu, Fan Wang, Tong Xu, Haoran Xin, Dejing Dou, Hui Xiong
Electric Vehicle (EV) has become a preferable choice in the modern transportation system due to its environmental and energy sustainability.
Multi-agent Reinforcement Learning reinforcement-learning +1
1 code implementation • 29 Jan 2021 • Haoran Xin, Xinjiang Lu, Tong Xu, Hao liu, Jingjing Gu, Dejing Dou, Hui Xiong
Second, a user-specific travel intention is formulated as an aggregation combining home-town preference and generic travel intention together, where the generic travel intention is regarded as a mixture of inherent intentions that can be learned by Neural Topic Model (NTM).
no code implementations • 28 Jan 2021 • Carter Blum, Hao liu, Hui Xiong
Electric vehicles have been rapidly increasing in usage, but stations to charge them have not always kept up with demand, so efficient routing of vehicles to stations is critical to operating at maximum efficiency.
no code implementations • 8 Jan 2021 • Hui Luo, Jingbo Zhou, Zhifeng Bao, Shuangli Li, J. Shane Culpepper, Haochao Ying, Hao liu, Hui Xiong
We design a novel multi-task learning model called MPR (short for Multi-level POI Recommendation), where each task aims to return the top-k POIs at a certain spatial granularity level.
no code implementations • 30 Dec 2020 • Jindong Han, Hao liu, HengShu Zhu, Hui Xiong, Dejing Dou
Specifically, we first propose a heterogeneous recurrent graph neural network to model the spatiotemporal autocorrelation among air quality and weather monitoring stations.
1 code implementation • 29 Dec 2020 • Le Yu, Leilei Sun, Bowen Du, Chuanren Liu, Weifeng Lv, Hui Xiong
Representation learning on heterogeneous graphs aims to obtain low-dimensional node representations that could preserve both node attributes and relation information.
Ranked #23 on Node Property Prediction on ogbn-mag
1 code implementation • 17 Dec 2020 • Jingbo Zhou, Shuangli Li, Liang Huang, Haoyi Xiong, Fan Wang, Tong Xu, Hui Xiong, Dejing Dou
The hierarchical attentive aggregation can capture spatial dependencies among atoms, as well as fuse the position-enhanced information with the capability of discriminating multiple spatial relations among atoms.
1 code implementation • 15 Dec 2020 • Junchen Ye, Leilei Sun, Bowen Du, Yanjie Fu, Hui Xiong
Graph Convolutional Network (GCN) has been widely applied in transportation demand prediction due to its excellent ability to capture non-Euclidean spatial dependence among station-level or regional transportation demands.
7 code implementations • 14 Dec 2020 • Haoyi Zhou, Shanghang Zhang, Jieqi Peng, Shuai Zhang, JianXin Li, Hui Xiong, Wancai Zhang
Many real-world applications require the prediction of long sequence time-series, such as electricity consumption planning.
Ranked #1 on Time Series Forecasting on ETTh2 (336) Univariate
no code implementations • Findings of the Association for Computational Linguistics 2020 • Lei Zhang, Runze Wang, Jingbo Zhou, Jingsong Yu, ZhenHua Ling, Hui Xiong
Continuous efforts have been devoted to language understanding (LU) for conversational queries with the fast and wide-spread popularity of voice assistants.
no code implementations • 26 Oct 2020 • Denghui Zhang, Yanchi Liu, Wei Cheng, Bo Zong, Jingchao Ni, Zhengzhang Chen, Haifeng Chen, Hui Xiong
Accurate air turbulence forecasting can help airlines avoid hazardous turbulence, guide the routes that keep passengers safe, maximize efficiency, and reduce costs.
no code implementations • 2 Oct 2020 • Wei Fan, Kunpeng Liu, Hao liu, Yong Ge, Hui Xiong, Yanjie Fu
In this journal version, we propose a novel interactive and closed-loop architecture to simultaneously model interactive reinforcement learning (IRL) and decision tree feedback (DTF).
no code implementations • 16 Sep 2020 • Denghui Zhang, Junming Liu, HengShu Zhu, Yanchi Liu, Lichen Wang, Pengyang Wang, Hui Xiong
However, it is still a challenging task since (1) the job title and job transition (job-hopping) data is messy which contains a lot of subjective and non-standard naming conventions for the same position (e. g., Programmer, Software Development Engineer, SDE, Implementation Engineer), (2) there is a large amount of missing title/transition information, and (3) one talent only seeks limited numbers of jobs which brings the incompleteness and randomness modeling job transition patterns.
no code implementations • 7 Sep 2020 • Denghui Zhang, Zixuan Yuan, Yanchi Liu, Fuzhen Zhuang, Haifeng Chen, Hui Xiong
Pre-trained language models such as BERT have achieved great success in a broad range of natural language processing tasks.
1 code implementation • 31 Aug 2020 • Yang Yang, Zhen-Qiang Sun, HengShu Zhu, Yanjie Fu, Hui Xiong, Jian Yang
To this end, we propose a Class-Incremental Learning without Forgetting (CILF) framework, which aims to learn adaptive embedding for processing novel class detection and model update in a unified framework.
no code implementations • 11 Aug 2020 • Yang Yang, Zhen-Qiang Sun, Hui Xiong, Jian Yang
Open set classification (OSC) tackles the problem of determining whether the data are in-class or out-of-class during inference, when only provided with a set of in-class examples at training time.
no code implementations • 21 Jul 2020 • Jingbo Zhou, Zhenwei Tang, Min Zhao, Xiang Ge, Fuzhen Zhuang, Meng Zhou, Liming Zou, Chenglei Yang, Hui Xiong
A mobile app interface usually consists of a set of user interface modules.
no code implementations • 11 Jul 2020 • Hao Liu, Ying Li, Yanjie Fu, Huaibo Mei, Jingbo Zhou, Xu Ma, Hui Xiong
Then, we introduce a general route search algorithm coupled with an efficient station binding method for efficient route candidate generation.
2 code implementations • 20 Jun 2020 • Le Yu, Leilei Sun, Bowen Du, Chuanren Liu, Hui Xiong, Weifeng Lv
Given a sequence of sets, where each set contains an arbitrary number of elements, the problem of temporal sets prediction aims to predict the elements in the subsequent set.
1 code implementation • 13 Apr 2020 • Jingjing Gu, Qiang Zhou, Jingyuan Yang, Yanchi Liu, Fuzhen Zhuang, Yanchao Zhao, Hui Xiong
Unlike the traditional dock-based systems, dockless bike-sharing systems are more convenient for users in terms of flexibility.
no code implementations • 28 Feb 2020 • Qingyu Guo, Fuzhen Zhuang, Chuan Qin, HengShu Zhu, Xing Xie, Hui Xiong, Qing He
On the one hand, we investigate the proposed algorithms by focusing on how the papers utilize the knowledge graph for accurate and explainable recommendation.
1 code implementation • 23 Feb 2020 • Chao Wang, HengShu Zhu, Chen Zhu, Chuan Qin, Hui Xiong
The recent development of online recommender systems has a focus on collaborative ranking from implicit feedback, such as user clicks and purchases.
no code implementations • 8 Feb 2020 • Mu Yuan, Lan Zhang, Xiang-Yang Li, Hui Xiong
With limited computing resources and stringent delay, given a data stream and a collection of applicable resource-hungry deep-learning models, we design a novel approach to adaptively schedule a subset of these models to execute on each data item, aiming to maximize the value of the model output (e. g., the number of high-confidence labels).
1 code implementation • 24 Nov 2019 • Weijia Zhang, Hao liu, Yanchi Liu, Jingbo Zhou, Hui Xiong
However, it is a non-trivial task for predicting citywide parking availability because of three major challenges: 1) the non-Euclidean spatial autocorrelation among parking lots, 2) the dynamic temporal autocorrelation inside of and between parking lots, and 3) the scarcity of information about real-time parking availability obtained from real-time sensors (e. g., camera, ultrasonic sensor, and GPS).
no code implementations • 21 Nov 2019 • Dazhong Shen, Qi Zhang, Tong Xu, HengShu Zhu, Wenjia Zhao, Zikai Yin, Peilun Zhou, Lihua Fang, Enhong Chen, Hui Xiong
To this end, in this paper, we present a machine learning-enhanced framework based on ensemble learning strategy, EL-Picker, for the automatic identification of seismic P-phase arrivals on continuous and massive waveforms.
3 code implementations • 7 Nov 2019 • Fuzhen Zhuang, Zhiyuan Qi, Keyu Duan, Dongbo Xi, Yongchun Zhu, HengShu Zhu, Hui Xiong, Qing He
In order to show the performance of different transfer learning models, over twenty representative transfer learning models are used for experiments.
no code implementations • 28 Aug 2019 • Yanan Wang, Tong Xu, Xin Niu, Chang Tan, Enhong Chen, Hui Xiong
Moreover, based on the temporally-dependent traffic information, we design a Graph Neural Network based model to represent relationships among multiple traffic lights, and the decision for each traffic light will be made in a distributed way by the deep Q-learning method.
1 code implementation • 7 Jun 2019 • Qi Liu, Zhenya Huang, Yu Yin, Enhong Chen, Hui Xiong, Yu Su, Guoping Hu
In EERNN, we simply summarize each student's state into an integrated vector and trace it with a recurrent neural network, where we design a bidirectional LSTM to learn the encoding of each exercise's content.
no code implementations • 29 May 2019 • Jian Liu, Pengpeng Zhao, Yanchi Liu, Victor S. Sheng, Fuzheng Zhuang, Jiajie Xu, Xiaofang Zhou, Hui Xiong
Then, we integrate the aesthetic features into a cross-domain network to transfer users' domain independent aesthetic preferences.
no code implementations • 1 May 2019 • Jinyin Chen, Mengmeng Su, Shijing Shen, Hui Xiong, Haibin Zheng
In this paper, comprehensive evaluation metrics are brought up for different adversarial attack methods.
no code implementations • 21 Dec 2018 • Chuan Qin, HengShu Zhu, Tong Xu, Chen Zhu, Liang Jiang, Enhong Chen, Hui Xiong
The wide spread use of online recruitment services has led to information explosion in the job market.
no code implementations • 1 Dec 2018 • Jinyin Chen, Haibin Zheng, Hui Xiong, Mengmeng Su
Inspired by the correlations between adversarial perturbations and object contour, slighter perturbations is produced via focusing on object contour features, which is more imperceptible and difficult to be defended, especially network add-on defense methods with the trade-off between perturbations filtering and contour feature loss.
no code implementations • 8 Oct 2018 • Chen Zhu, HengShu Zhu, Hui Xiong, Chao Ma, Fang Xie, Pengliang Ding, Pan Li
To this end, in this paper, we propose a novel end-to-end data-driven model based on Convolutional Neural Network (CNN), namely Person-Job Fit Neural Network (PJFNN), for matching a talent qualification to the requirements of a job.
no code implementations • 30 Apr 2018 • Constantine Vitt, Darinka Dentcheva, Hui Xiong
We develop a new approach to solving classification problems, which is bases on the theory of coherent measures of risk and risk sharing ideas.
no code implementations • 8 Dec 2017 • Chen Zhu, HengShu Zhu, Hui Xiong, Pengliang Ding, Fang Xie
To this end, in this paper, we propose a new research paradigm for recruitment market analysis by leveraging unsupervised learning techniques for automatically discovering recruitment market trends based on large-scale recruitment data.
no code implementations • 17 May 2017 • Yanjie Fu, Charu Aggarwal, Srinivasan Parthasarathy, Deepak S. Turaga, Hui Xiong
This formulation incorporates multiple aspects such as (i) an upper limit on the total execution time of detectors (ii) diversity in the space of algorithms and features, and (iii) meta-learning for evaluating the cost and utility of detectors.
2 code implementations • 2 Mar 2017 • Zijun Yao, Yifan Sun, Weicong Ding, Nikhil Rao, Hui Xiong
Word evolution refers to the changing meanings and associations of words throughout time, as a byproduct of human language evolution.
no code implementations • 25 Jul 2016 • Kai Zhang, Chuanren Liu, Jie Zhang, Hui Xiong, Eric Xing, Jieping Ye
Given a matrix A of size m by n, state-of-the-art randomized algorithms take O(m * n) time and space to obtain its low-rank decomposition.
no code implementations • 25 Sep 2014 • Liang Wu, Hui Xiong, Liang Du, Bo Liu, Guandong Xu, Yong Ge, Yanjie Fu, Yuanchun Zhou, Jianhui Li
Specifically, this method can capture both the inherent information in the source codes and the semantic information hidden in the comments, descriptions, and identifiers of the source codes.