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» Data reduction for weighted and outlier-resistant clustering
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SODA
2012
ACM
223views Algorithms» more  SODA 2012»
11 years 7 months ago
Data reduction for weighted and outlier-resistant clustering
Statistical data frequently includes outliers; these can distort the results of estimation procedures and optimization problems. For this reason, loss functions which deemphasize ...
Dan Feldman, Leonard J. Schulman
ICASSP
2010
IEEE
13 years 4 months ago
Swift: Scalable weighted iterative sampling for flow cytometry clustering
Flow cytometry (FC) is a powerful technology for rapid multivariate analysis and functional discrimination of cells. Current FC platforms generate large, high-dimensional datasets...
Iftekhar Naim, Suprakash Datta, Gaurav Sharma, Jam...
SDM
2004
SIAM
162views Data Mining» more  SDM 2004»
13 years 5 months ago
Subspace Clustering of High Dimensional Data
Clustering suffers from the curse of dimensionality, and similarity functions that use all input features with equal relevance may not be effective. We introduce an algorithm that...
Carlotta Domeniconi, Dimitris Papadopoulos, Dimitr...
ICASSP
2011
IEEE
12 years 8 months ago
Detection of anomalous events from unlabeled sensor data in smart building environments
This paper presents a robust unsupervised learning approach for detection of anomalies in patterns of human behavior using multi-modal smart environment sensor data. We model the ...
Padmini Jaikumar, Aca Gacic, Burton Andrews, Micha...
ICASSP
2010
IEEE
13 years 4 months ago
Aspect-model-based reference speaker weighting
We propose an aspect-model-based reference speaker weighting. The main idea of the approach is that the adapted model is a linear combination of a set of reference speakers like r...
Seongjun Hahm, Yuichi Ohkawa, Masashi Ito, Motoyuk...