Hongyuan Zha mainly investigates Artificial intelligence, Information retrieval, Machine learning, Cluster analysis and Social network. His studies deal with areas such as Ranking, Theoretical computer science and Pattern recognition as well as Artificial intelligence. His biological study spans a wide range of topics, including Representation, Support vector machine and Citation.
His research in the fields of Recommender system and Collaborative filtering overlaps with other disciplines such as Order. His work deals with themes such as Subspace topology, Data mining, Graph partition, Algorithm and Eigenvalues and eigenvectors, which intersect with Cluster analysis. His Algorithm research incorporates elements of Multigraph, Combinatorics and Dimensionality reduction.
Hongyuan Zha mostly deals with Artificial intelligence, Machine learning, Algorithm, Information retrieval and Pattern recognition. Hongyuan Zha mostly deals with Cluster analysis in his studies of Artificial intelligence. His Cluster analysis study frequently links to adjacent areas such as Graph partition.
His Algorithm research is multidisciplinary, incorporating elements of Matrix, Mathematical optimization and Dimensionality reduction. His World Wide Web research extends to Information retrieval, which is thematically connected. His work is dedicated to discovering how Search engine, Relevance are connected with Ranking and other disciplines.
His primary areas of study are Artificial intelligence, Machine learning, Theoretical computer science, Point process and Mathematical optimization. The Artificial intelligence study combines topics in areas such as Data mining and Pattern recognition. His Machine learning study incorporates themes from Sequence and Interval.
His Theoretical computer science research includes elements of Graph, Inference, Leverage and Graph. His work carried out in the field of Point process brings together such families of science as Event, Algorithm, Function and Maximum likelihood. He works mostly in the field of Event, limiting it down to topics relating to Cluster analysis and, in certain cases, Mixture model, as a part of the same area of interest.
Hongyuan Zha spends much of his time researching Artificial intelligence, Machine learning, Point process, Pattern recognition and Theoretical computer science. His Artificial intelligence research includes themes of Markov decision process and Data mining. His Reinforcement learning and Deep learning study in the realm of Machine learning interacts with subjects such as Self paced, Data modeling and Subject-matter expert.
Hongyuan Zha combines subjects such as Entropy, Entropy and Hyperplane with his study of Pattern recognition. The study incorporates disciplines such as Event, Matching, Statistical model, Graph and Key in addition to Theoretical computer science. In his research, Ranking is intimately related to Information retrieval, which falls under the overarching field of Artificial neural network.
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Principal Manifolds and Nonlinear Dimensionality Reduction via Tangent Space Alignment
Zhenyue Zhang;Hongyuan Zha.
SIAM Journal on Scientific Computing (2005)
A min-max cut algorithm for graph partitioning and data clustering
C.H.Q. Ding;Xiaofeng He;Xiaofeng He;Hongyuan Zha;Ming Gu.
international conference on data mining (2001)
Principal Manifolds and Nonlinear Dimension Reduction via Local Tangent Space Alignment
Zhenyue Zhang;Hongyuan Zha.
arXiv: Learning (2002)
Sensor positioning in wireless ad-hoc sensor networks using multidimensional scaling
Xiang Ji;Hongyuan Zha.
international conference on computer communications (2004)
Spectral Relaxation for K-means Clustering
Hongyuan Zha;Xiaofeng He;Chris Ding;Ming Gu.
neural information processing systems (2001)
R1-PCA: rotational invariant L 1 -norm principal component analysis for robust subspace factorization
Chris Ding;Ding Zhou;Xiaofeng He;Hongyuan Zha.
international conference on machine learning (2006)
Two supervised learning approaches for name disambiguation in author citations
Hui Han;Lee Giles;Hongyuan Zha;Cheng Li.
acm/ieee joint conference on digital libraries (2004)
Automatic document metadata extraction using support vector machines
Hui Han;C.L. Giles;E. Manavoglu;Hongyuan Zha.
acm ieee joint conference on digital libraries (2003)
Bipartite graph partitioning and data clustering
Hongyuan Zha;Xiaofeng He;Chris Ding;Horst Simon.
conference on information and knowledge management (2001)
Like like alike: joint friendship and interest propagation in social networks
Shuang-Hong Yang;Bo Long;Alex Smola;Narayanan Sadagopan.
the web conference (2011)
Profile was last updated on December 6th, 2021.
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