Titlebook: Advances in Knowledge Discovery and Data Mining; 23rd Pacific-Asia Co Qiang Yang,Zhi-Hua Zhou,Sheng-Jun Huang Conference proceedings 2019 S

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A Dynamic Resource Management Problem,arieties of features from ECG and using them to build a classifier. However, ECG usually presents high inter- and intra-subjects variability both in morphology and timing, hence, it’s difficult for predesigned features to accurately depict the fluctuation patterns of each heartbeat. To this end, we

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The Core, Superadditivity, and Convexity,ctly based on a number of previous practices and outcomes in their learning process. KT leverages machine learning and data mining techniques to provide better assessment, supportive learning feedback and adaptive instructions. In this paper, we propose a novel model called Dynamic Student Classific

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https://doi.org/10.1007/978-3-662-60715-2ic signal control results in people’s waste of time in commuting, road rage in the traffic jam, and high cost for city operation. Recently, deep reinforcement learning (DRL) approaches shed lights to better optimize traffic signal plans according to the feedback received from the environment. Most o

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健壯

A Cloud Architecture for Service Robots,ater-supply, and sales predictions. In this paper, we study the case of retailers’ sales forecasting on Tmall—the world’s leading online B2C platform. By analyzing the data, we have two main observations, i.e., . after we group different groups of retails and a . after we transform the sales (target

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