Search Results - "Zhou, Hua"

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  1. 1

    A brief introduction to weakly supervised learning by Zhou, Zhi-Hua

    Published in National science review (01-01-2018)
    “…Abstract Supervised learning techniques construct predictive models by learning from a large number of training examples, where each training example has a…”
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  3. 3

    Side effects of methotrexate therapy for rheumatoid arthritis: A systematic review by Wang, Wanying, Zhou, Hua, Liu, Liang

    Published in European journal of medicinal chemistry (05-10-2018)
    “…Methotrexate (MTX) is used as an anchor disease-modifying anti-rheumatic drugs (DMARDs) in treating rheumatoid arthritis (RA) because of its potent efficacy…”
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  4. 4

    A Review on Multi-Label Learning Algorithms by Zhang, Min-Ling, Zhou, Zhi-Hua

    “…Multi-label learning studies the problem where each example is represented by a single instance while associated with a set of labels simultaneously. During…”
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  5. 5

    Automatic Age Estimation Based on Facial Aging Patterns by XIN GENG, ZHOU, Zhi-Hua, SMITH-MILES, Kate

    “…While recognition of most facial variations, such as identity, expression, and gender, has been extensively studied, automatic age estimation has rarely been…”
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  6. 6

    Deep forest by Zhou, Zhi-Hua, Feng, Ji

    Published in National science review (01-01-2019)
    “…Abstract Current deep-learning models are mostly built upon neural networks, i.e. multiple layers of parameterized differentiable non-linear modules that can…”
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  7. 7

    Multi-Label Learning with Global and Local Label Correlation by Zhu, Yue, Kwok, James T., Zhou, Zhi-Hua

    “…It is well-known that exploiting label correlations is important to multi-label learning. Existing approaches either assume that the label correlations are…”
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  8. 8

    Exploratory Undersampling for Class-Imbalance Learning by Liu, Xu-Ying, Wu, Jianxin, Zhou, Zhi-Hua

    “…Undersampling is a popular method in dealing with class-imbalance problems, which uses only a subset of the majority class and thus is very efficient. The main…”
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  9. 9

    A high-performance topological bulk laser based on band-inversion-induced reflection by Shao, Zeng-Kai, Chen, Hua-Zhou, Wang, Suo, Mao, Xin-Rui, Yang, Zhen-Qian, Wang, Shao-Lei, Wang, Xing-Xiang, Hu, Xiao, Ma, Ren-Min

    Published in Nature nanotechnology (01-01-2020)
    “…Topological insulators are materials that behave as insulators in the bulk and as conductors at the edge or surface due to the particular configuration of…”
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  10. 10

    Adaptive error feedback regulation problem for 1D wave equation by Guo, Wei, Zhou, Hua‐cheng, Krstic, Miroslav

    “…Summary By using the adaptive control approach, we solve the error feedback regulator problem for the one‐dimensional wave equation with a general harmonic…”
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  11. 11

    Directional Fluid Transport in Thin Porous Materials and its Functional Applications by Zhao, Yan, Wang, Hongxia, Zhou, Hua, Lin, Tong

    “…Directional fluid motion driven by the surface property of solid substrate is highly desirable for manipulating microfluidic liquid and collecting water from…”
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  12. 12

    One-Pass Learning with Incremental and Decremental Features by Hou, Chenping, Zhou, Zhi-Hua

    “…In many real tasks the features are evolving, with some features vanished and some other features being augmented. For example, in environment monitoring some…”
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  13. 13

    Facial Age Estimation by Learning from Label Distributions by Geng, Xin, Yin, Chao, Zhou, Zhi-Hua

    “…One of the main difficulties in facial age estimation is that the learning algorithms cannot expect sufficient and complete training data. Fortunately, the…”
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  14. 14

    Optimal Margin Distribution Machine by Zhang, Teng, Zhou, Zhi-Hua

    “…Support Vector Machine (SVM) has always been one of the most successful learning algorithms, with the central idea of maximizing the minimum margin , i.e., the…”
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  15. 15

    Towards Making Unlabeled Data Never Hurt by Li, Yu-Feng, Zhou, Zhi-Hua

    “…It is usually expected that learning performance can be improved by exploiting unlabeled data, particularly when the number of labeled data is limited…”
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  16. 16

    Improve Computer-Aided Diagnosis With Machine Learning Techniques Using Undiagnosed Samples by Li, Ming, Zhou, Zhi-Hua

    “…In computer-aided diagnosis (CAD), machine learning techniques have been widely applied to learn a hypothesis from diagnosed samples to assist the medical…”
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  17. 17

    Revealing the missing dimension at an exceptional point by Chen, Hua-Zhou, Liu, Tuo, Luan, Hong-Yi, Liu, Rong-Juan, Wang, Xing-Yuan, Zhu, Xue-Feng, Li, Yuan-Bo, Gu, Zhong-Ming, Liang, Shan-Jun, Gao, He, Lu, Ling, Ge, Li, Zhang, Shuang, Zhu, Jie, Ma, Ren-Min

    Published in Nature physics (01-05-2020)
    “…The radiation of electromagnetic and mechanical waves depends not only on the intrinsic properties of the emitter but also on the surrounding environment. This…”
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  18. 18

    Multi-Label Learning with Emerging New Labels by Zhu, Yue, Ting, Kai Ming, Zhou, Zhi-Hua

    “…In a multi-label learning task, an object possesses multiple concepts where each concept is represented by a class label. Previous studies on multi-label…”
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  19. 19

    Active Learning by Querying Informative and Representative Examples by Huang, Sheng-Jun, Jin, Rong, Zhou, Zhi-Hua

    “…Active learning reduces the labeling cost by iteratively selecting the most valuable data to query their labels. It has attracted a lot of interests given the…”
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  20. 20

    Multiple imputation: review of theory, implementation and software by Harel, Ofer, Zhou, Xiao-Hua

    Published in Statistics in medicine (20-07-2007)
    “…Missing data is a common complication in data analysis. In many medical settings missing data can cause difficulties in estimation, precision and inference…”
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