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» Adaptive K-Means Clustering
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NIPS
2000
14 years 11 months ago
A Silicon Primitive for Competitive Learning
Competitive learning is a technique for training classification and clustering networks. We have designed and fabricated an 11transistor primitive, that we term an automaximizing ...
David Hsu, Miguel Figueroa, Chris Diorio
SC
2003
ACM
15 years 3 months ago
Dyn-MPI: Supporting MPI on Non Dedicated Clusters
Distributing data is a fundamental problem in implementing efficient distributed-memory parallel programs. The problem becomes more difficult in environments where the participa...
D. Brent Weatherly, David K. Lowenthal, Mario Naka...
JPDC
2006
100views more  JPDC 2006»
14 years 9 months ago
Dyn-MPI: Supporting MPI on medium-scale, non-dedicated clusters
Distributing data is a fundamental problem in implementing efficient distributed-memory parallel programs. The problem becomes more difficult in environments where the participati...
D. Brent Weatherly, David K. Lowenthal, Mario Naka...
IEEECIT
2010
IEEE
14 years 8 months ago
Tessellating Cell Shapes for Geographical Clustering
This paper investigates the energy-saving organization of sensor nodes in large wireless sensor networks. Due to a random deployment used in many application scenarios, much more n...
Jakob Salzmann, Ralf Behnke, Dirk Timmermann
INTERSPEECH
2010
14 years 4 months ago
Unsupervised discovery and training of maximally dissimilar cluster models
One of the difficult problems of acoustic modeling for Automatic Speech Recognition (ASR) is how to adequately model the wide variety of acoustic conditions which may be present i...
Françoise Beaufays, Vincent Vanhoucke, Bria...