What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Statistics
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.
His most cited work include:
- Principal Manifolds and Nonlinear Dimensionality Reduction via Tangent Space Alignment (1179 citations)
- A min-max cut algorithm for graph partitioning and data clustering (733 citations)
- Sensor positioning in wireless ad-hoc sensor networks using multidimensional scaling (546 citations)
What are the main themes of his work throughout his whole career to date?
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.
He most often published in these fields:
- Artificial intelligence (43.09%)
- Machine learning (23.94%)
- Algorithm (17.29%)
What were the highlights of his more recent work (between 2015-2021)?
- Artificial intelligence (43.09%)
- Machine learning (23.94%)
- Theoretical computer science (11.70%)
In recent papers he was focusing on the following fields of study:
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.
Between 2015 and 2021, his most popular works were:
- Sequential Recommendation with User Memory Networks (187 citations)
- Unsupervised Deep Learning for Optical Flow Estimation. (163 citations)
- Iterative Learning with Open-set Noisy Labels (121 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Statistics
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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