Search Results for author: Jing Ma

Found 40 papers, 11 papers with code

HiTRANS: A Hierarchical Transformer Network for Nested Named Entity Recognition

no code implementations Findings (EMNLP) 2021 Zhiwei Yang, Jing Ma, Hechang Chen, Yunke Zhang, Yi Chang

Specifically, we first utilize a two-phase module to generate span representations by aggregating context information based on a bottom-up and top-down transformer network.

named-entity-recognition Nested Named Entity Recognition +1

AnswerFact: Fact Checking in Product Question Answering

no code implementations EMNLP 2020 Wenxuan Zhang, Yang Deng, Jing Ma, Wai Lam

Product-related question answering platforms nowadays are widely employed in many E-commerce sites, providing a convenient way for potential customers to address their concerns during online shopping.

Fact Checking Misinformation +1

Zero-Shot Rumor Detection with Propagation Structure via Prompt Learning

no code implementations2 Dec 2022 Hongzhan Lin, Pengyao Yi, Jing Ma, Haiyun Jiang, Ziyang Luo, Shuming Shi, Ruifang Liu

The spread of rumors along with breaking events seriously hinders the truth in the era of social media.

Interpreting Unfairness in Graph Neural Networks via Training Node Attribution

1 code implementation25 Nov 2022 Yushun Dong, Song Wang, Jing Ma, Ninghao Liu, Jundong Li

In this paper, we study a novel problem of interpreting GNN unfairness through attributing it to the influence of training nodes.

Private Semi-supervised Knowledge Transfer for Deep Learning from Noisy Labels

no code implementations3 Nov 2022 Qiuchen Zhang, Jing Ma, Jian Lou, Li Xiong, Xiaoqian Jiang

PATE combines an ensemble of "teacher models" trained on sensitive data and transfers the knowledge to a "student" model through the noisy aggregation of teachers' votes for labeling unlabeled public data which the student model will be trained on.

Transfer Learning

CLEAR: Generative Counterfactual Explanations on Graphs

no code implementations16 Oct 2022 Jing Ma, Ruocheng Guo, Saumitra Mishra, Aidong Zhang, Jundong Li

Counterfactual explanations promote explainability in machine learning models by answering the question "how should an input instance be perturbed to obtain a desired predicted label?".

Counterfactual Explanation Explanation Generation

Towards Training Graph Neural Networks with Node-Level Differential Privacy

no code implementations10 Oct 2022 Qiuchen Zhang, Jing Ma, Jian Lou, Carl Yang, Li Xiong

Furthermore, we analyze the privacy degradation caused by the sampling process dependent on the differentially private PageRank results during model training and propose a differentially private GNN (DPGNN) algorithm to further protect node features and achieve rigorous node-level differential privacy.

A Coarse-to-fine Cascaded Evidence-Distillation Neural Network for Explainable Fake News Detection

1 code implementation COLING 2022 Zhiwei Yang, Jing Ma, Hechang Chen, Hongzhan Lin, Ziyang Luo, Yi Chang

Existing fake news detection methods aim to classify a piece of news as true or false and provide veracity explanations, achieving remarkable performances.

Fake News Detection

Learning Causal Effects on Hypergraphs

no code implementations7 Jul 2022 Jing Ma, Mengting Wan, Longqi Yang, Jundong Li, Brent Hecht, Jaime Teevan

Hypergraphs provide an effective abstraction for modeling multi-way group interactions among nodes, where each hyperedge can connect any number of nodes.

Mapping Emulation for Knowledge Distillation

no code implementations21 May 2022 Jing Ma, Xiang Xiang, Zihan Zhang, Yuwen Tan, Yiming Wan, Zhigang Zeng, DaCheng Tao

A new geometric perspective is presented to view such a problem as aligning generated distributions between the teacher and student.

Federated Learning Knowledge Distillation

Empowering Next POI Recommendation with Multi-Relational Modeling

no code implementations24 Apr 2022 Zheng Huang, Jing Ma, Yushun Dong, Natasha Zhang Foutz, Jundong Li

Noticeably, LBSNs have offered unparalleled access to abundant heterogeneous relational information about users and POIs (including user-user social relations, such as families or colleagues; and user-POI visiting relations).

Representation Learning

A Weakly Supervised Propagation Model for Rumor Verification and Stance Detection with Multiple Instance Learning

no code implementations6 Apr 2022 Ruichao Yang, Jing Ma, Hongzhan Lin, Wei Gao

The diffusion of rumors on microblogs generally follows a propagation tree structure, that provides valuable clues on how an original message is transmitted and responded by users over time.

Multiple Instance Learning Stance Classification +1

A Frustratingly Simple Approach for End-to-End Image Captioning

no code implementations30 Jan 2022 Ziyang Luo, Yadong Xi, Rongsheng Zhang, Jing Ma

Before training the captioning models, an extra object detector is utilized to recognize the objects in the image at first.

Image Captioning Text Generation

Learning Fair Node Representations with Graph Counterfactual Fairness

no code implementations10 Jan 2022 Jing Ma, Ruocheng Guo, Mengting Wan, Longqi Yang, Aidong Zhang, Jundong Li

In this framework, we generate counterfactuals corresponding to perturbations on each node's and their neighbors' sensitive attributes.

Data Augmentation Fairness

Coarse-To-Fine Incremental Few-Shot Learning

1 code implementation24 Nov 2021 Xiang Xiang, Yuwen Tan, Qian Wan, Jing Ma

Such images form a new training set (i. e., support set) so that the incremental model is hoped to recognize a basenji (i. e., query) as a basenji next time.

class-incremental learning Few-Shot Learning +1

Malicious Mode Attack on EV Coordinated Charging Load and MIADRC Defense Strategy

no code implementations26 Oct 2021 Yichen Zhou, Weidong Liu, Jing Ma, Xinghao Zhen, Yonggang Li

Further, to mitigate the impact of MMA, a defense strategy based on multi-index information active disturbance rejection control is proposed to improve the stability and anti-disturbance ability of the power system, which considers the impact factors of both mode damping and disturbance compensation.

Analyzing the Implicit Position Encoding Ability of Transformer Decoder

no code implementations29 Sep 2021 Ziyang Luo, Yadong Xi, Jing Ma, Xiaoxi Mao, Changjie Fan

A common limitation of Transformer Encoder's self-attention mechanism is that it cannot automatically capture the information of word order, so one needs to feed the explicit position encodings into the target model.

Language Modelling

Communication Efficient Generalized Tensor Factorization for Decentralized Healthcare Networks

no code implementations3 Sep 2021 Jing Ma, Qiuchen Zhang, Jian Lou, Li Xiong, Sivasubramanium Bhavani, Joyce C. Ho

Tensor factorization has been proved as an efficient unsupervised learning approach for health data analysis, especially for computational phenotyping, where the high-dimensional Electronic Health Records (EHRs) with patients' history of medical procedures, medications, diagnosis, lab tests, etc., are converted to meaningful and interpretable medical concepts.

Computational Phenotyping

Temporal Network Embedding via Tensor Factorization

no code implementations22 Aug 2021 Jing Ma, Qiuchen Zhang, Jian Lou, Li Xiong, Joyce C. Ho

Representation learning on static graph-structured data has shown a significant impact on many real-world applications.

Link Prediction Network Embedding +1

Multi-objective optimization and explanation for stroke risk assessment in Shanxi province

no code implementations29 Jul 2021 Jing Ma, Yiyang Sun, Junjie Liu, Huaxiong Huang, Xiaoshuang Zhou, Shixin Xu

The experimental results showed that the QIDNN model with 7 interactive features achieve the state-of-art accuracy $83. 25\%$.

Federated Graph Classification over Non-IID Graphs

1 code implementation NeurIPS 2021 Han Xie, Jing Ma, Li Xiong, Carl Yang

Federated learning has emerged as an important paradigm for training machine learning models in different domains.

Classification Dynamic Time Warping +4

Assessing the Causal Impact of COVID-19 Related Policies on Outbreak Dynamics: A Case Study in the US

1 code implementation29 May 2021 Jing Ma, Yushun Dong, Zheng Huang, Daniel Mietchen, Jundong Li

Besides, as the confounders may be time-varying during COVID-19 (e. g., vigilance of residents changes in the course of the pandemic), it is even more difficult to capture them.

Learning from Crowds by Modeling Common Confusions

2 code implementations24 Dec 2020 Zhendong Chu, Jing Ma, Hongning Wang

Crowdsourcing provides a practical way to obtain large amounts of labeled data at a low cost.

Image Classification

Debunking Rumors on Twitter with Tree Transformer

no code implementations COLING 2020 Jing Ma, Wei Gao

Rumors are manufactured with no respect for accuracy, but can circulate quickly and widely by {``}word-of-post{''} through social media conversations.

Transferable Multi-level Attention Neural Network for Accurate Prediction of Quantum Chemistry Properties via Multi-task Learning

no code implementations30 Jun 2020 Liqiang Lin, Qingqing Jia, Zheng Cheng, Yanyan Jiang, Yanwen Guo, Jing Ma

The development of efficient models for predicting specific properties through machine learning is of great importance for the innovation of chemistry and material science.

Drug Discovery Formation Energy +1

Spatio-Temporal Tensor Sketching via Adaptive Sampling

no code implementations21 Jun 2020 Jing Ma, Qiuchen Zhang, Joyce C. Ho, Li Xiong

In this paper, we propose SkeTenSmooth, a novel tensor factorization framework that uses adaptive sampling to compress the tensor in a temporally streaming fashion and preserves the underlying global structure.

Management

Review-guided Helpful Answer Identification in E-commerce

1 code implementation13 Mar 2020 Wenxuan Zhang, Wai Lam, Yang Deng, Jing Ma

In this paper, we propose the Review-guided Answer Helpfulness Prediction (RAHP) model that not only considers the interactions between QA pairs but also investigates the opinion coherence between the answer and crowds' opinions reflected in the reviews, which is another important factor to identify helpful answers.

Answer Selection Community Question Answering

Privacy-Preserving Tensor Factorization for Collaborative Health Data Analysis

no code implementations26 Aug 2019 Jing Ma, Qiuchen Zhang, Jian Lou, Joyce C. Ho, Li Xiong, Xiaoqian Jiang

We propose DPFact, a privacy-preserving collaborative tensor factorization method for computational phenotyping using EHR.

Computational Phenotyping Privacy Preserving

Sentence-Level Evidence Embedding for Claim Verification with Hierarchical Attention Networks

no code implementations ACL 2019 Jing Ma, Wei Gao, Shafiq Joty, Kam-Fai Wong

Claim verification is generally a task of verifying the veracity of a given claim, which is critical to many downstream applications.

Claim Verification

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