J
Jiawei Han
Researcher at University of Illinois at Urbana–Champaign
Publications - 1302
Citations - 155054
Jiawei Han is an academic researcher from University of Illinois at Urbana–Champaign. The author has contributed to research in topics: Cluster analysis & Knowledge extraction. The author has an hindex of 168, co-authored 1233 publications receiving 143427 citations. Previous affiliations of Jiawei Han include Georgia Institute of Technology & United States Army Research Laboratory.
Papers
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Proceedings Article
Large-scale spectral clustering on graphs
TL;DR: The key idea is to repeatedly generate a small number of "supernodes" connected to the regular nodes, in order to compress the original graph into a sparse bipartite graph.
Journal ArticleDOI
Regression Cubes with Lossless Compression and Aggregation
TL;DR: This paper proposes a fundamentally new class of measures, compressible measures, in order to support efficient computation of the statistical models, and substantially reduces the memory usage and the overall response time for statistical analysis of multidimensional data.
Using Graph Model for Face Analysis
Deng Cai,Xiaofei He,Jiawei Han +2 more
TL;DR: It is shown that LPP provides a more general framework for subspace learning and a natural solution to the small sample issue in LDA.
Book ChapterDOI
Community trend outlier detection using soft temporal pattern mining
TL;DR: This paper proposes an effective two-step procedure to detect community trend outliers, which first model the normal evolutionary behavior of communities across time using soft patterns discovered from the dataset, and proposes effective measures to evaluate chances of an object deviating from thenormal evolutionary patterns.
Book ChapterDOI
Linear discriminant dimensionality reduction
TL;DR: This paper aims at finding a subset of features, based on which the learnt linear transformation via LDA maximizes the Fisher criterion, and proposes to integrate Fisher score and LDA in a unified framework, namely Linear Discriminant Dimensionality Reduction (LDDR).