Hierarchical maximum-margin clustering
We present a hierarchical maximum-margin clustering method for unsupervised data
analysis. Our method extends beyond flat maximum-margin clustering, and performs …
analysis. Our method extends beyond flat maximum-margin clustering, and performs …
Consensus of clusterings based on high-order dissimilarities
Over the years, many clustering algorithms have been developed, handling different issues
such as cluster shape, density or noise. Most clustering algorithms require a similarity …
such as cluster shape, density or noise. Most clustering algorithms require a similarity …
Statistical properties of the single linkage hierarchical clustering estimator
D Zhu, DP Guralnik, X Wang, X Li, B Moran - arXiv preprint arXiv …, 2015 - arxiv.org
Distance-based hierarchical clustering (HC) methods are widely used in unsupervised data
analysis but few authors take account of uncertainty in the distance data. We incorporate a …
analysis but few authors take account of uncertainty in the distance data. We incorporate a …
Node-merging method in passive network topology detection
L He, Q Wei - 2015 IEEE Advanced Information Technology …, 2015 - ieeexplore.ieee.org
In order to establish a clear picture of Internet topology, our Node-Merging Method (NMM)
tries to make use of only the protocol information between two nodes, especially the hop …
tries to make use of only the protocol information between two nodes, especially the hop …
Maximum Likelihood Estimation for Single Linkage Hierarchical Clustering
D Zhu, DP Guralnik, X Wang, X Li, B Moran - arXiv preprint arXiv …, 2015 - arxiv.org
We derive a statistical model for estimation of a dendrogram from single linkage hierarchical
clustering (SLHC) that takes account of uncertainty through noise or corruption in the …
clustering (SLHC) that takes account of uncertainty through noise or corruption in the …
Toward Scene Recognition by Discovering Semantic Structures and Parts
GT Zhou - 2015 - summit.sfu.ca
Scene recognition is a fundamental and open problem in computer vision. It is an essential
component of a variety of real-world applications, including image search, robotics, social …
component of a variety of real-world applications, including image search, robotics, social …