Zhiwen Yu mostly deals with Artificial intelligence, Data mining, Machine learning, Cluster analysis and Social network. His Artificial intelligence study combines topics from a wide range of disciplines, such as Computer vision and Pattern recognition. His study in the fields of Visualization under the domain of Data mining overlaps with other disciplines such as Incentive.
His Machine learning study combines topics in areas such as Event and Key. His work in the fields of Cluster analysis, such as Consensus clustering, Correlation clustering, Clustering high-dimensional data and Affinity propagation, intersects with other areas such as Data source. His work carried out in the field of Social network brings together such families of science as Computer security and Data science.
His scientific interests lie mostly in Artificial intelligence, Machine learning, Data mining, Pattern recognition and Cluster analysis. Artificial intelligence is closely attributed to Computer vision in his study. His Data mining research includes elements of Affinity propagation and Clustering high-dimensional data.
His Pattern recognition study frequently draws connections between related disciplines such as Linear subspace. His work on Cluster analysis deals in particular with Correlation clustering and Fuzzy clustering. His Correlation clustering study focuses mostly on Consensus clustering and CURE data clustering algorithm.
His primary areas of study are Artificial intelligence, Machine learning, Deep learning, Cluster analysis and Field. The concepts of his Artificial intelligence study are interwoven with issues in Computer vision and Pattern recognition. The study incorporates disciplines such as Multi-task learning, Feature extraction and Robustness in addition to Machine learning.
His research integrates issues of Artificial neural network, Activity recognition, Data modeling and Compression in his study of Deep learning. His Cluster analysis research includes themes of Data mining and k-nearest neighbors algorithm. His Field study integrates concerns from other disciplines, such as Key and Data science.
Zhiwen Yu mainly focuses on Artificial intelligence, Machine learning, Deep learning, Feature extraction and Data science. His studies in Artificial intelligence integrate themes in fields like Encoder and Pattern recognition. His Machine learning research integrates issues from Multi-task learning, Point of interest and Class.
His Deep learning research is multidisciplinary, relying on both Artificial neural network, Activity recognition and Knowledge extraction. Zhiwen Yu combines subjects such as Social network, Field, The Internet, Consumer behaviour and Social media with his study of Data science. In his study, which falls under the umbrella issue of Ensemble learning, Order, Mobile computing and Dynamic pricing is strongly linked to Data modeling.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Sensor-Based Activity Recognition
Liming Chen;J. Hoey;C. D. Nugent;D. J. Cook.
systems man and cybernetics (2012)
Mobile Crowd Sensing and Computing: The Review of an Emerging Human-Powered Sensing Paradigm
Bin Guo;Zhu Wang;Zhiwen Yu;Yu Wang.
ACM Computing Surveys (2015)
From participatory sensing to Mobile Crowd Sensing
Bin Guo;Zhiwen Yu;Xingshe Zhou;Daqing Zhang.
international conference on pervasive computing (2014)
TV Program Recommendation for Multiple Viewers Based on user Profile Merging
Zhiwen Yu;Xingshe Zhou;Yanbin Hao;Jianhua Gu.
User Modeling and User-adapted Interaction (2006)
Opportunistic IoT: Exploring the harmonious interaction between human and the internet of things
Bin Guo;Daqing Zhang;Zhu Wang;Zhiwen Yu.
Journal of Network and Computer Applications (2013)
Supporting Context-Aware Media Recommendations for Smart Phones
Zhiwen Yu;Xingshe Zhou;Daqing Zhang;Chung-Yau Chin.
IEEE Pervasive Computing (2006)
Personalized Travel Package With Multi-Point-of-Interest Recommendation Based on Crowdsourced User Footprints
Zhiwen Yu;Huang Xu;Zhe Yang;Bin Guo.
IEEE Transactions on Human-Machine Systems (2016)
The Emergence of Social and Community Intelligence
Daqing Zhang;Bin Guo;Zhiwen Yu.
IEEE Computer (2011)
Graph-based consensus clustering for class discovery from gene expression data
Zhiwen Yu;Hau-San Wong;Hongqiang Wang.
From Participatory Sensing to Mobile Crowd Sensing
Bin Guo;Zhiwen Yu;Daqing Zhang;Xingshe Zhou.
arXiv: Human-Computer Interaction (2014)
Profile was last updated on December 6th, 2021.
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