7 citations · 37 across the 10 of their papers we have counts for
8 papers · 1 filter
Clustering by Deep Nearest Neighbor Descent (D-NND): A Density-based Parameter-Insensitive Clustering Method
Teng Qiu, Yongjie Li
Most density-based clustering methods largely rely on how well the underlying density is estimated. However, density estimation itself is also a challenging problem, especially the…
IT-Dendrogram: A New Member of the In-Tree (IT) Clustering Family
Teng Qiu, Yongjie Li
Previously, we proposed a physically-inspired method to construct data points into an effective in-tree (IT) structure, in which the underlying cluster structure in the dataset is…
A general framework for the IT-based clustering methods
Teng Qiu, Yongjie Li
Previously, we proposed a physically inspired rule to organize the data points in a sparse yet effective structure, called the in-tree (IT) graph, which is able to capture a wide c…
Nonparametric Nearest Neighbor Descent Clustering based on Delaunay Triangulation
Teng Qiu, Yongjie Li
In our physically inspired in-tree (IT) based clustering algorithm and the series after it, there is only one free parameter involved in computing the potential value of each point…
Clustering by Descending to the Nearest Neighbor in the Delaunay Graph Space
Teng Qiu, Yongjie Li
In our previous works, we proposed a physically-inspired rule to organize the data points into an in-tree (IT) structure, in which some undesired edges are allowed to occur. By rem…
An Effective Semi-supervised Divisive Clustering Algorithm
Teng Qiu, Yongjie Li
Nowadays, data are generated massively and rapidly from scientific fields as bioinformatics, neuroscience and astronomy to business and engineering fields. Cluster analysis, as one…