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    Chapter and Conference Paper

    An Effective Implementation of a Direct Spanning Tree Representation in GAs

    This paper presents an effective implementation based on predecessor vectors of a genetic algorithm using a direct tree representation. The main operations associated with crossovers and mutations can be achie...

    Yu Li in Applications of Evolutionary Computing (2001)

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    Chapter and Conference Paper

    Representing EHRs with Temporal Tree and Sequential Pattern Mining for Similarity Computing

    The ability to rapidly identify at scale patients that are similar based on their electronic health records (EHRs) is fundamental for a number of clinical informatics applications, such as clinical decision su...

    Suresh Pokharel, Guido Zuccon, Yu Li in Advanced Data Mining and Applications (2020)

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    Chapter and Conference Paper

    Discriminative Features Generation for Mortality Prediction in ICU

    Effective methods for mortality prediction for Intensive Care Unit (ICU) patients assist health professionals by producing alerts ahead of time regarding the critical changing degeneration of a patient’s healt...

    Suresh Pokharel, Zhenkun Shi, Guido Zuccon, Yu Li in Advanced Data Mining and Applications (2020)

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    Chapter and Conference Paper

    CLMB: Deep Contrastive Learning for Robust Metagenomic Binning

    The reconstruction of microbial genomes from large metagenomic datasets is a critical procedure for finding uncultivated microbial populations and defining their microbial functional roles. To achieve that, we...

    Pengfei Zhang, Zhengyuan Jiang, Yixuan Wang in Research in Computational Molecular Biology (2022)

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    Chapter and Conference Paper

    GRU-Attention Interpretable Knowledge Tracking Model with Forgetting Law for Intelligent Education System

    The advent of intelligent education systems and widespread distance learning have revolutionized the educational landscape. Extracting meaningful insights from this wealth of information is crucial for improvi...

    Haonan Li, Yu Li, Zhenguo Zhang in Artificial Intelligence Logic and Applications (2023)

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    Chapter and Conference Paper

    Quantifying Occupant Behavior Uncertainty in Spatio-Temporal Visual Comfort Assessment of National Fitness Halls: A Machine Learning-Based Co-simulation Framework

    Occupant behavior has been recognized as the main factor influencing visual comfort gaps between simulated and actual conditions. However, existing daylight and glare simulation methods mostly fail to deal wit...

    Yu Li, Lingling Li, Pengyuan Shen, Xue Cui in Computer-Aided Architectural Design. INTER… (2023)