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ICASSP
2010
IEEE
15 years 6 months ago
Learning from high-dimensional noisy data via projections onto multi-dimensional ellipsoids
In this paper, we examine the problem of learning from noisecontaminated data in high-dimensional space. A new learning approach based on projections onto multi-dimensional ellips...
Liuling Gong, Dan Schonfeld
PKDD
2010
Springer
166views Data Mining» more  PKDD 2010»
15 years 4 months ago
A Cluster-Level Semi-supervision Model for Interactive Clustering
Abstract. Semi-supervised clustering models, that incorporate user provided constraints to yield meaningful clusters, have recently become a popular area of research. In this paper...
Avinava Dubey, Indrajit Bhattacharya, Shantanu God...
BIBE
2009
IEEE
131views Bioinformatics» more  BIBE 2009»
15 years 9 months ago
Learning Scaling Coefficient in Possibilistic Latent Variable Algorithm from Complex Diagnosis Data
—The Possibilistic Latent Variable (PLV) clustering algorithm is a powerful tool for the analysis of complex datasets due to its robustness toward data distributions of different...
Zong-Xian Yin
CLASSIFICATION
2008
111views more  CLASSIFICATION 2008»
15 years 6 months ago
Probabilistic D-Clustering
: We present a new iterative method for probabilistic clustering of data. Given clusters, their centers and the distances of data points from these centers, the probability of clus...
Adi Ben-Israel, Cem Iyigun
CVPR
2012
IEEE
13 years 8 months ago
Group action induced distances for averaging and clustering Linear Dynamical Systems with applications to the analysis of dynami
We introduce a framework for defining a distance on the (non-Euclidean) space of Linear Dynamical Systems (LDSs). The proposed distance is induced by the action of the group of o...
Bijan Afsari, Rizwan Chaudhry, Avinash Ravichandra...