Search Results for author: Hui Xu

Found 28 papers, 6 papers with code

SHAPE: A Sample-adaptive Hierarchical Prediction Network for Medication Recommendation

no code implementations9 Sep 2023 Sicen Liu, Xiaolong Wang, Jingcheng Du, Yongshuai Hou, Xianbing Zhao, Hui Xu, Hui Wang, Yang Xiang, Buzhou Tang

Effectively medication recommendation with complex multimorbidity conditions is a critical task in healthcare.

Exploring the Limits of Historical Information for Temporal Knowledge Graph Extrapolation

no code implementations29 Aug 2023 Yi Xu, Junjie Ou, Hui Xu, Luoyi Fu, Lei Zhou, Xinbing Wang, Chenghu Zhou

To this end, we investigate the limits of historical information for temporal knowledge graph extrapolation and propose a new event forecasting model called Contrastive Event Network (CENET) based on a novel training framework of historical contrastive learning.

Contrastive Learning Knowledge Graphs

Physics-Assisted Reduced-Order Modeling for Identifying Dominant Features of Transonic Buffet

no code implementations23 May 2023 Jing Wang, Hairun Xie, Miao Zhang, Hui Xu

The dominant latent space further reveals a strong relevance with the key flow features located in the boundary layers downstream of shock.

Temporal Knowledge Graph Reasoning with Historical Contrastive Learning

1 code implementation20 Nov 2022 Yi Xu, Junjie Ou, Hui Xu, Luoyi Fu

Simultaneously, it trains representations of queries to investigate whether the current moment depends more on historical or non-historical events by launching contrastive learning.

Contrastive Learning

Joint nnU-Net and Radiomics Approaches for Segmentation and Prognosis of Head and Neck Cancers with PET/CT images

no code implementations18 Nov 2022 Hui Xu, Yihao Li, Wei Zhao, Gwenolé Quellec, Lijun Lu, Mathieu Hatt

Then 3D nnU-Net architecture was adopted to automatic segmentation of primary tumor and lymph nodes synchronously. Based on predicted segmentation, ten conventional features and 346 standardized radiomics features were extracted for each patient.

Automatic Check-Out via Prototype-based Classifier Learning from Single-Product Exemplars

4 code implementations The European Conference on Computer Vision (ECCV) 2022 Hao Chen, Xiu-Shen Wei, Faen Zhang, Yang shen, Hui Xu, Liang Xiao

Automatic Check-Out (ACO) aims to accurately predict the presence and count of each category of products in check-out images, where a major challenge is the significant domain gap between training data (single-product exemplars) and test data (check-out images).


KnowledgeShovel: An AI-in-the-Loop Document Annotation System for Scientific Knowledge Base Construction

no code implementations6 Oct 2022 Shao Zhang, Yuting Jia, Hui Xu, Dakuo Wang, Toby Jia-Jun Li, Ying Wen, Xinbing Wang, Chenghu Zhou

Constructing a comprehensive, accurate, and useful scientific knowledge base is crucial for human researchers synthesizing scientific knowledge and for enabling Al-driven scientific discovery.

CATNet: Cross-event Attention-based Time-aware Network for Medical Event Prediction

no code implementations29 Apr 2022 Sicen Liu, Xiaolong Wang, Yang Xiang, Hui Xu, Hui Wang, Buzhou Tang

It is a time-aware, event-aware and task-adaptive method with the following advantages: 1) modeling heterogeneous information and temporal information in a unified way and considering temporal irregular characteristics locally and globally respectively, 2) taking full advantage of correlations among different types of events via cross-event attention.

Time Series Analysis

Diverse Preference Augmentation with Multiple Domains for Cold-start Recommendations

no code implementations1 Apr 2022 Yan Zhang, Changyu Li, Ivor W. Tsang, Hui Xu, Lixin Duan, Hongzhi Yin, Wen Li, Jie Shao

Motivated by the idea of meta-augmentation, in this paper, by treating a user's preference over items as a task, we propose a so-called Diverse Preference Augmentation framework with multiple source domains based on meta-learning (referred to as MetaDPA) to i) generate diverse ratings in a new domain of interest (known as target domain) to handle overfitting on the case of sparse interactions, and to ii) learn a preference model in the target domain via a meta-learning scheme to alleviate cold-start issues.

Domain Adaptation Meta-Learning +1

DeepShovel: An Online Collaborative Platform for Data Extraction in Geoscience Literature with AI Assistance

no code implementations21 Feb 2022 Shao Zhang, Yuting Jia, Hui Xu, Ying Wen, Dakuo Wang, Xinbing Wang

Geoscientists, as well as researchers in many fields, need to read a huge amount of literature to locate, extract, and aggregate relevant results and data to enable future research or to build a scientific database, but there is no existing system to support this use case well.

The China Trade Shock and the ESG Performances of US firms

no code implementations28 Jan 2022 Hui Xu, Yue Wu

Exploiting a trade policy in which US congress granted China the Permanent Normal Trade Relations and the resulting change in expected tariff rates on Chinese imports, we find that greater import competition from China leads to an increase in the US company's ESG performance.

Multimodal data matters: language model pre-training over structured and unstructured electronic health records

1 code implementation25 Jan 2022 Sicen Liu, Xiaolong Wang, Yongshuai Hou, Ge Li, Hui Wang, Hui Xu, Yang Xiang, Buzhou Tang

As two important textual modalities in electronic health records (EHR), both structured data (clinical codes) and unstructured data (clinical narratives) have recently been increasingly applied to the healthcare domain.

Decision Making Language Modelling +1

DROID: Minimizing the Reality Gap using Single-Shot Human Demonstration

no code implementations22 Feb 2021 Ya-Yen Tsai, Hui Xu, Zihan Ding, Chong Zhang, Edward Johns, Bidan Huang

One of the main challenges of transferring the policy learned in a simulated environment to real world, is the discrepancy between the dynamics of the two environments.


Turbulence suppression by streamwise-varying wall rotation in pipe flow

no code implementations6 Jan 2021 Xu Liu, Hongbo Zhu, Rui Wang, Yan Bao, Dai Zhou, Zhaolong Han, Chuanqing Zhou, Yegao Qu, Hui Xu

Two control parameters, which are velocity amplitude and wavelength, are considered.

Fluid Dynamics

High-Order Relation Construction and Mining for Graph Matching

no code implementations9 Oct 2020 Hui Xu, Liyao Xiang, Youmin Le, Xiaoying Gan, Yuting Jia, Luoyi Fu, Xinbing Wang

Iterated line graphs are introduced for the first time to describe such high-order information, based on which we present a new graph matching method, called High-order Graph Matching Network (HGMN), to learn not only the local structural correspondence, but also the hyperedge relations across graphs.

Graph Matching Vocal Bursts Intensity Prediction

GPRInvNet: Deep Learning-Based Ground Penetrating Radar Data Inversion for Tunnel Lining

no code implementations12 Dec 2019 Bin Liu, Yuxiao Ren, Hanchi Liu, Hui Xu, Zhengfang Wang, Anthony G. Cohn, Peng Jiang

The results have demonstrated that the GPRInvNet is capable of effectively reconstructing complex tunnel lining defects with clear boundaries.

GPR Time Series Analysis

Regression via Arbitrary Quantile Modeling

1 code implementation13 Nov 2019 Faen Zhang, Xinyu Fan, Hui Xu, Pengcheng Zhou, Yujian He, Junlong Liu

In the regression problem, L1 and L2 are the most commonly used loss functions, which produce mean predictions with different biases.


Detecting Deep Neural Network Defects with Data Flow Analysis

no code implementations5 Sep 2019 Jiazhen Gu, Huanlin Xu, Yangfan Zhou, Xin Wang, Hui Xu, Michael Lyu

Deep neural networks (DNNs) are shown to be promising solutions in many challenging artificial intelligence tasks.

Object Recognition

HM-NAS: Efficient Neural Architecture Search via Hierarchical Masking

no code implementations31 Aug 2019 Shen Yan, Biyi Fang, Faen Zhang, Yu Zheng, Xiao Zeng, Hui Xu, Mi Zhang

Without the constraint imposed by the hand-designed heuristics, our searched networks contain more flexible and meaningful architectures that existing weight sharing based NAS approaches are not able to discover.

Neural Architecture Search

Strongly Independent Matrices and Rigidity of $\times A$-Invariant Measures on $n$-Torus

no code implementations6 Aug 2019 Huichi Huang, Hanfeng Li, Enhui Shi, Hui Xu

We introduce the concept of strongly independent matrices over any field, and prove the existence of such matrices for certain fields and the non-existence for algebraically closed fields.

Dynamical Systems 37A05, 37A25, 37A46, 43A05, 28C10, 12E05

Nektar++: enhancing the capability and application of high-fidelity spectral/$hp$ element methods

no code implementations8 Jun 2019 David Moxey, Chris D. Cantwell, Yan Bao, Andrea Cassinelli, Giacomo Castiglioni, Sehun Chun, Emilia Juda, Ehsan Kazemi, Kilian Lackhove, Julian Marcon, Gianmarco Mengaldo, Douglas Serson, Michael Turner, Hui Xu, Joaquim Peiró, Robert M. Kirby, Spencer J. Sherwin

Nektar++ is an open-source framework that provides a flexible, high-performance and scalable platform for the development of solvers for partial differential equations using the high-order spectral/$hp$ element method.

Mathematical Software Numerical Analysis Numerical Analysis Fluid Dynamics

DeepObfuscation: Securing the Structure of Convolutional Neural Networks via Knowledge Distillation

no code implementations27 Jun 2018 Hui Xu, Yuxin Su, Zirui Zhao, Yangfan Zhou, Michael R. Lyu, Irwin King

Our obfuscation approach is very effective to protect the critical structure of a deep learning model from being exposed to attackers.

Cryptography and Security

On Secure and Usable Program Obfuscation: A Survey

no code implementations3 Oct 2017 Hui Xu, Yangfan Zhou, Yu Kang, Michael R. Lyu

On the other hand, the performance requirement for model-oriented obfuscation approaches is too weak to develop practical program obfuscation solutions.

Cryptography and Security Software Engineering

N-Version Obfuscation: Impeding Software Tampering Replication with Program Diversity

no code implementations8 Jun 2015 Hui Xu, Yangfan Zhou, Michael R. Lyu

Our idea is to impede the replication of tampering via program diversification, and thus increasing the complexity to break the whole software system.

Cryptography and Security Programming Languages

Convolution and convolution-root properties of long-tailed distributions

no code implementations29 Jan 2015 Hui Xu, Sergey Foss, Yuebao Wang

These examples help to provide further insights and, in particular, to show that the properties to be both long-tailed and so-called "generalised subexponential" are not preserved under the convolution roots.

Probability 60E05, 60F10, 60G50

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