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» On Approximating the Average Distance Between Points
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NN
1998
Springer
177views Neural Networks» more  NN 1998»
14 years 11 months ago
Soft vector quantization and the EM algorithm
The relation between hard c-means (HCM), fuzzy c-means (FCM), fuzzy learning vector quantization (FLVQ), soft competition scheme (SCS) of Yair et al. (1992) and probabilistic Gaus...
Ethem Alpaydin
119
Voted
NIPS
2001
15 years 1 months ago
Global Coordination of Local Linear Models
High dimensional data that lies on or near a low dimensional manifold can be described by a collection of local linear models. Such a description, however, does not provide a glob...
Sam T. Roweis, Lawrence K. Saul, Geoffrey E. Hinto...
91
Voted
STOC
2007
ACM
100views Algorithms» more  STOC 2007»
15 years 12 months ago
Reordering buffers for general metric spaces
In the reordering buffer problem, we are given an input sequence of requests for service each of which corresponds to a point in a metric space. The cost of serving the requests h...
Matthias Englert, Harald Räcke, Matthias West...
105
Voted
MOBICOM
2009
ACM
15 years 6 months ago
Lifetime and coverage guarantees through distributed coordinate-free sensor activation
Wireless Sensor Networks are emerging as a key sensing technology, with diverse military and civilian applications. In these networks, a large number of sensors perform distribute...
Gaurav S. Kasbekar, Yigal Bejerano, Saswati Sarkar
ICPR
2006
IEEE
15 years 5 months ago
Fast Linear Discriminant Analysis Using Binary Bases
Linear Discriminant Analysis (LDA) is a widely used technique for pattern classification. It seeks the linear projection of the data to a low dimensional subspace where the data ...
Feng Tang, Hai Tao