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Liu, Kai
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Deep item-based collaborative filtering for top-N recommendation
Xue F., He X., Wang X., Xu J., Liu K., Hong R. ACM Transactions on Information Systems 37(3): 1-25, 2019. Type: Article
Recommender systems are an essential component in digital platforms, nudging consumers toward more efficient decision making by predicting and presenting products and services in a personalized ranking order that is of top interest. By...
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Nov 19 2019
A two-stage framework for 3D face reconstruction from RGBD images
Wang K., Wang X., Pan Z., Liu K. IEEE Transactions on Pattern Analysis and Machine Intelligence 36(8): 1493-1504, 2014. Type: Article
The application of MS Kinect is popular since it provides the user with color images with depth in real time. Related research in computer graphics has been focused on getting structured information out of the raw data. Although this i...
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Apr 8 2015
Data scheduling for multi-item requests in multi-channel on-demand broadcast environments
Liu K., Lee V., Leung K. MobiDE 2008 (Proceedings of the 7th ACM International Workshop on Data Engineering for Wireless and Mobile Access, Vancouver, Canada, Jun 13, 2008) 47-54, 2008. Type: Proceedings
Liu, Lee, and Leung introduce a new algorithm, called dynamic urgency and productivity (DUP), to overcome two problems they identify as key obstacles to optimizing data scheduling for active jobs: the request starvation and broadcast m...
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Mar 29 2010
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