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AAAI
2006
14 years 11 months ago
When Is Constrained Clustering Beneficial, and Why?
Several researchers have illustrated that constraints can improve the results of a variety of clustering algorithms. However, there can be a large variation in this improvement, e...
Kiri Wagstaff, Sugato Basu, Ian Davidson
KDD
2006
ACM
107views Data Mining» more  KDD 2006»
15 years 10 months ago
Out-of-core frequent pattern mining on a commodity PC
In this work we focus on the problem of frequent itemset mining on large, out-of-core data sets. After presenting a characterization of existing out-of-core frequent itemset minin...
Gregory Buehrer, Srinivasan Parthasarathy, Amol Gh...
AIME
2009
Springer
15 years 2 months ago
Data-Efficient Information-Theoretic Test Selection
We use the concept of conditional mutual information (MI) to approach problems involving the selection of variables in the area of medical diagnosis. Computing MI requires estimate...
Marianne Mueller, Rómer Rosales, Harald Ste...
ICS
1995
Tsinghua U.
15 years 1 months ago
A Data Cache with Multiple Caching Strategies Tuned to Different Types of Locality
Current data cache organizations fail to deliver high performance in scalar processors for many vector applications. There are two main reasons for this loss of performance: the u...
Antonio González, Carlos Aliagas, Mateo Val...
ISVC
2007
Springer
15 years 4 months ago
Gradient-Based Hand Tracking Using Silhouette Data
Optical motion capture can be classified as an inference problem: given the data produced by a set of cameras, the aim is to extract the hidden state, which in this case encodes t...
Paris Kaimakis, Joan Lasenby