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NIPS
2004
13 years 10 months ago
Maximising Sensitivity in a Spiking Network
We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
Anthony J. Bell, Lucas C. Parra
ADHOC
2007
121views more  ADHOC 2007»
13 years 8 months ago
Power-aware single- and multipath geographic routing in sensor networks
Nodes in a sensor network, operating on power limited batteries, must save power to minimize the need for battery replacement. We note that the range of transmission has a signiï¬...
Shibo Wu, K. Selçuk Candan
BIOINFORMATICS
2006
142views more  BIOINFORMATICS 2006»
13 years 8 months ago
Intervention in a family of Boolean networks
Motivation: Intervention in a gene regulatory network is used to avoid undesirable states, such as those associated with a disease. Several types of intervention have been studied...
Ashish Choudhary, Aniruddha Datta, Michael L. Bitt...
BMCBI
2005
169views more  BMCBI 2005»
13 years 8 months ago
Genetic interaction motif finding by expectation maximization - a novel statistical model for inferring gene modules from synthe
Background: Synthetic lethality experiments identify pairs of genes with complementary function. More direct functional associations (for example greater probability of membership...
Yan Qi 0003, Ping Ye, Joel S. Bader
NN
1998
Springer
177views Neural Networks» more  NN 1998»
13 years 8 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