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» Minimum Spanning Tree Based Clustering Algorithms
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109
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ICML
2008
IEEE
16 years 3 months ago
ManifoldBoost: stagewise function approximation for fully-, semi- and un-supervised learning
We introduce a boosting framework to solve a classification problem with added manifold and ambient regularization costs. It allows for a natural extension of boosting into both s...
Nicolas Loeff, David A. Forsyth, Deepak Ramachandr...
171
Voted
APBC
2004
132views Bioinformatics» more  APBC 2004»
15 years 4 months ago
A Novel Feature Selection Method to Improve Classification of Gene Expression Data
This paper introduces a novel method for minimum number of gene (feature) selection for a classification problem based on gene expression data with an objective function to maximi...
Liang Goh, Qun Song, Nikola K. Kasabov
128
Voted
ICASSP
2009
IEEE
15 years 9 months ago
Decentralized variational filtering for simultaneous sensor localization and target tracking in binary sensor networks
Resource limitations in wireless sensor networks have put stringent constraints on distributed signal processing. In this paper, we propose a cluster-based decentralized variation...
Jing Teng, Hichem Snoussi, Cédric Richard
139
Voted
ACCV
2009
Springer
15 years 9 months ago
Natural Image Segmentation with Adaptive Texture and Boundary Encoding
We present a novel algorithm for unsupervised segmentation of natural images that harnesses the principle of minimum description length (MDL). Our method is based on observations ...
Shankar Rao, Hossein Mobahi, Allen Y. Yang, Shanka...
117
Voted
DAC
2003
ACM
16 years 3 months ago
Multilevel floorplanning/placement for large-scale modules using B*-trees
We present in this paper a multilevel floorplanning/placement framework based on the B*-tree representation, called MB*-tree, to handle the floorplanning and packing for large-sca...
Hsun-Cheng Lee, Yao-Wen Chang, Jer-Ming Hsu, Hanna...