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NIPS
2008
13 years 9 months ago
Stochastic Relational Models for Large-scale Dyadic Data using MCMC
Stochastic relational models (SRMs) [15] provide a rich family of choices for learning and predicting dyadic data between two sets of entities. The models generalize matrix factor...
Shenghuo Zhu, Kai Yu, Yihong Gong
AES
2008
Springer
133views Cryptology» more  AES 2008»
13 years 7 months ago
Alternative neural networks to estimate the scour below spillways
Artificial neural networks (ANN's) are associated with difficulties like lack of success in a given problem and unpredictable level of accuracy that could be achieved. In eve...
H. Md. Azamathulla, M. C. Deo, P. B. Deolalikar
JCB
2007
130views more  JCB 2007»
13 years 7 months ago
Bayesian Inference of MicroRNA Targets from Sequence and Expression Data
MicroRNAs (miRNAs) regulate a large proportion of mammalian genes by hybridizing to targeted messenger RNAs (mRNAs) and down-regulating their translation into protein. Although mu...
Jim C. Huang, Quaid Morris, Brendan J. Frey
GECCO
2009
Springer
199views Optimization» more  GECCO 2009»
14 years 4 days ago
Using behavioral exploration objectives to solve deceptive problems in neuro-evolution
Encouraging exploration, typically by preserving the diversity within the population, is one of the most common method to improve the behavior of evolutionary algorithms with dece...
Jean-Baptiste Mouret, Stéphane Doncieux
ICML
2005
IEEE
14 years 8 months ago
Optimal assignment kernels for attributed molecular graphs
We propose a new kernel function for attributed molecular graphs, which is based on the idea of computing an optimal assignment from the atoms of one molecule to those of another ...
Andreas Zell, Florian Sieker, Holger Fröhlich...