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ICPR
2006
IEEE
14 years 8 months ago
Learning Wormholes for Sparsely Labelled Clustering
Distance functions are an important component in many learning applications. However, the correct function is context dependent, therefore it is advantageous to learn a distance f...
Eng-Jon Ong, Richard Bowden
ASUNAM
2011
IEEE
12 years 7 months ago
Evolutionary Clustering and Analysis of Bibliographic Networks
—In this paper, we study the problem of evolutionary clustering of multi-typed objects in a heterogeneous bibliographic network. The traditional methods of homogeneous clustering...
Manish Gupta, Charu C. Aggarwal, Jiawei Han, Yizho...
SBACPAD
2005
IEEE
176views Hardware» more  SBACPAD 2005»
14 years 1 months ago
Analyzing and Improving Clustering Based Sampling for Microprocessor Simulation
The time required to simulate a complete benchmark program using the cycle-accurate model of a microprocessor can be prohibitively high. One of the proposed methodologies, represe...
Yue Luo, Ajay Joshi, Aashish Phansalkar, Lizy Kuri...
PDPTA
2007
13 years 8 months ago
Two Graph Algorithms On an Associative Computing Model
- The MASC (for Multiple Associative Computing) model is a SIMD model enhanced with associative properties and multiple synchronous instruction streams (IS). A number of algorithms...
Mingxian Jin, Johnnie W. Baker
WWW
2010
ACM
14 years 2 months ago
Empirical comparison of algorithms for network community detection
Detecting clusters or communities in large real-world graphs such as large social or information networks is a problem of considerable interest. In practice, one typically chooses...
Jure Leskovec, Kevin J. Lang, Michael W. Mahoney