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CIKM
2010
Springer
15 years 1 months ago
SHRINK: a structural clustering algorithm for detecting hierarchical communities in networks
Community detection is an important task for mining the structure and function of complex networks. Generally, there are several different kinds of nodes in a network which are c...
Jianbin Huang, Heli Sun, Jiawei Han, Hongbo Deng, ...
KDD
2006
ACM
165views Data Mining» more  KDD 2006»
16 years 3 months ago
Training linear SVMs in linear time
Linear Support Vector Machines (SVMs) have become one of the most prominent machine learning techniques for highdimensional sparse data commonly encountered in applications like t...
Thorsten Joachims
SDM
2010
SIAM
153views Data Mining» more  SDM 2010»
15 years 4 months ago
The Generalized Dimensionality Reduction Problem
The dimensionality reduction problem has been widely studied in the database literature because of its application for concise data representation in a variety of database applica...
Charu C. Aggarwal
KDD
2008
ACM
172views Data Mining» more  KDD 2008»
16 years 3 months ago
Structured metric learning for high dimensional problems
The success of popular algorithms such as k-means clustering or nearest neighbor searches depend on the assumption that the underlying distance functions reflect domain-specific n...
Jason V. Davis, Inderjit S. Dhillon
CPHYSICS
2006
124views more  CPHYSICS 2006»
15 years 3 months ago
Collision-free spatial hash functions for structural analysis of billion-vertex chemical bond networks
State-of-the-art molecular dynamics (MD) simulations generate massive datasets involving billion-vertex chemical bond networks, which makes data mining based on graph algorithms s...
Cheng Zhang, Bhupesh Bansal, Paulo S. Branicio, Ra...