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ICDM
2002
IEEE
158views Data Mining» more  ICDM 2002»
15 years 9 months ago
Adaptive dimension reduction for clustering high dimensional data
It is well-known that for high dimensional data clustering, standard algorithms such as EM and the K-means are often trapped in local minimum. Many initialization methods were pro...
Chris H. Q. Ding, Xiaofeng He, Hongyuan Zha, Horst...
CAIP
1997
Springer
125views Image Analysis» more  CAIP 1997»
15 years 8 months ago
An Algorithm for Intrinsic Dimensionality Estimation
Abstract. In this paper a new method for analyzing the intrinsic dimensionality (ID) of low dimensional manifolds in high dimensional feature spaces is presented. The basic idea is...
Jörg Bruske, Gerald Sommer
UAI
2008
15 years 6 months ago
Improving Gradient Estimation by Incorporating Sensor Data
An efficient policy search algorithm should estimate the local gradient of the objective function, with respect to the policy parameters, from as few trials as possible. Whereas m...
Gregory Lawrence, Stuart J. Russell
BMCBI
2005
107views more  BMCBI 2005»
15 years 4 months ago
Protein subcellular localization prediction for Gram-negative bacteria using amino acid subalphabets and a combination of multip
Background: Predicting the subcellular localization of proteins is important for determining the function of proteins. Previous works focused on predicting protein localization in...
Jiren Wang, Wing-Kin Sung, Arun Krishnan, Kuo-Bin ...
ICDE
2005
IEEE
115views Database» more  ICDE 2005»
16 years 6 months ago
Snapshot Queries: Towards Data-Centric Sensor Networks
In this paper we introduce the idea of snapshot queries for energy efficient data acquisition in sensor networks. Network nodes generate models of their surrounding environment th...
Yannis Kotidis