We present an efficient dynamic algorithm for clustering undirected graphs, whose edge property is changing continuously. The algorithm maintains clusters of high quality in pres...
Local pattern mining algorithms generate sets of patterns, which are typically not directly useful and have to be further processed before actual application or interpretation. Ra...
Nonlinear dimensionality reduction methods often rely on the nearest-neighbors graph to extract low-dimensional embeddings that reliably capture the underlying structure of high-d...
Mass-produced goods tend to be highly standardized in order to maximize manufacturing efficiencies. Some high-value goods with limited production quantities remain much less stand...
We consider a novel problem of learning an optimal matching, in an online fashion, between two feature spaces that are organized as taxonomies. We formulate this as a multi-armed ...
In recent years, spectral clustering method has gained attentions because of its superior performance compared to other traditional clustering algorithms such as K-means algorithm...
In this paper we formulate spectral clustering in directed graphs as an optimization problem, the objective being a weighted cut in the directed graph. This objective extends seve...
Given a set of objects V with a dissimilarity measure between pairs of objects in V , a PoCluster is a collection of sets P ⊂ powerset(V ) partially ordered by the ⊂ relation ...
Jinze Liu, Qi Zhang, Wei Wang 0010, Leonard McMill...
With recent advances in sensory and mobile computing technology, enormous amounts of data about moving objects are being collected. One important application with such data is aut...
Xiaolei Li, Jiawei Han, Sangkyum Kim, Hector Gonza...
How do blogs cite and influence each other? How do such links evolve? Does the popularity of old blog posts drop exponentially with time? These are some of the questions that we ...
Jure Leskovec, Mary McGlohon, Christos Faloutsos, ...