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NIPS
2008
14 years 11 months ago
Kernel Measures of Independence for non-iid Data
Many machine learning algorithms can be formulated in the framework of statistical independence such as the Hilbert Schmidt Independence Criterion. In this paper, we extend this c...
Xinhua Zhang, Le Song, Arthur Gretton, Alex J. Smo...
SIGMOD
2008
ACM
107views Database» more  SIGMOD 2008»
15 years 9 months ago
Outlier-robust clustering using independent components
How can we efficiently find a clustering, i.e. a concise description of the cluster structure, of a given data set which contains an unknown number of clusters of different shape ...
Christian Böhm, Christos Faloutsos, Claudia P...
GPB
2008
41views more  GPB 2008»
14 years 9 months ago
Gene Expression Data Classification Using Consensus Independent Component Analysis
Chun-Hou Zheng, De-Shuang Huang, Xiangzhen Kong, X...
ICA
2007
Springer
15 years 1 months ago
Infinite Sparse Factor Analysis and Infinite Independent Components Analysis
Abstract. A nonparametric Bayesian extension of Independent Components Analysis (ICA) is proposed where observed data Y is modelled as a linear superposition, G, of a potentially i...
David Knowles, Zoubin Ghahramani
DRM
2005
Springer
15 years 3 months ago
Improved watermark detection for spread-spectrum based watermarking using independent component analysis
This paper presents an efficient blind watermark detection/decoding scheme for spread spectrum (SS) based watermarking, exploiting the fact that in SS-based embedding schemes the ...
Hafiz Malik, Ashfaq A. Khokhar, Rashid Ansari