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ENGL
2007
180views more  ENGL 2007»
13 years 7 months ago
Biological Data Mining for Genomic Clustering Using Unsupervised Neural Learning
— The paper aims at designing a scheme for automatic identification of a species from its genome sequence. A set of 64 three-tuple keywords is first generated using the four type...
Shreyas Sen, Seetharam Narasimhan, Amit Konar
SDM
2008
SIAM
139views Data Mining» more  SDM 2008»
13 years 8 months ago
Simultaneous Unsupervised Learning of Disparate Clusterings
Most clustering algorithms produce a single clustering for a given data set even when the data can be clustered naturally in multiple ways. In this paper, we address the difficult...
Prateek Jain, Raghu Meka, Inderjit S. Dhillon
ICASSP
2010
IEEE
13 years 7 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
ACL
1993
13 years 8 months ago
Distributional Clustering of English Words
We describe and evaluate experimentally a method for clustering words according to their distribution in particular syntactic contexts. Words are represented by the relative frequ...
Fernando C. N. Pereira, Naftali Tishby, Lillian Le...
NCI
2004
142views Neural Networks» more  NCI 2004»
13 years 8 months ago
A competitive and cooperative learning approach to robust data clustering
This paper presents a new semi-competitive learning paradigm named Competitive and Cooperative Learning (CCL), in which seed points not only compete each other for updating to ada...
Yiu-ming Cheung