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AUSDM
2008
Springer
211views Data Mining» more  AUSDM 2008»
15 years 5 months ago
LBR-Meta: An Efficient Algorithm for Lazy Bayesian Rules
LBR is a highly accurate classification algorithm, which lazily constructs a single Bayesian rule for each test instance at classification time. However, its computational complex...
Zhipeng Xie
147
Voted
VTS
2007
IEEE
203views Hardware» more  VTS 2007»
15 years 10 months ago
Multiple Bit Upset Tolerant Memory Using a Selective Cycle Avoidance Based SEC-DED-DAEC Code
Conventional error correcting code (ECC) schemes used in memories and caches cannot correct double bit errors caused by a single event upset (SEU). As memory density increases, mu...
Avijit Dutta, Nur A. Touba
139
Voted
AUSAI
2004
Springer
15 years 7 months ago
Using Classification to Evaluate the Output of Confidence-Based Association Rule Mining
Abstract. Association rule mining is a data mining technique that reveals interesting relationships in a database. Existing approaches employ different parameters to search for int...
Stefan Mutter, Mark Hall, Eibe Frank
131
Voted
ICDM
2006
IEEE
154views Data Mining» more  ICDM 2006»
15 years 9 months ago
Mining and Predicting Duplication over Peer-to-Peer Query Streams
Many previous works of data mining user queries in Peer-to-Peer systems focused their attention on the distribution of query contents. However, few has been done towards a better ...
Shicong Meng, Yifeng Shao, Cong Shi, Dingyi Han, Y...
162
Voted
TNN
2008
182views more  TNN 2008»
15 years 3 months ago
Large-Scale Maximum Margin Discriminant Analysis Using Core Vector Machines
Abstract--Large-margin methods, such as support vector machines (SVMs), have been very successful in classification problems. Recently, maximum margin discriminant analysis (MMDA) ...
Ivor Wai-Hung Tsang, András Kocsor, James T...