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GECCO
2005
Springer
175views Optimization» more  GECCO 2005»
16 years 22 min ago
Nonlinear feature extraction using a neuro genetic hybrid
Feature extraction is a process that extracts salient features from observed variables. It is considered a promising alternative to overcome the problems of weight and structure o...
Yung-Keun Kwon, Byung Ro Moon
UAI
1998
15 years 7 months ago
The Bayesian Structural EM Algorithm
In recent years there has been a flurry of works on learning Bayesian networks from data. One of the hard problems in this area is how to effectively learn the structure of a beli...
Nir Friedman
TNN
2008
177views more  TNN 2008»
15 years 6 months ago
Adaptive Importance Sampling to Accelerate Training of a Neural Probabilistic Language Model
Previous work on statistical language modeling has shown that it is possible to train a feed-forward neural network to approximate probabilities over sequences of words, resulting...
Yoshua Bengio, Jean-Sébastien Senecal
SIAMDM
2010
113views more  SIAMDM 2010»
15 years 1 months ago
The VPN Problem with Concave Costs
We consider the following network design problem. We are given an undirected network with costs on the edges, a set of terminals, and an upper bound for each terminal limiting the ...
Samuel Fiorini, Gianpaolo Oriolo, Laura Sanit&agra...
INFOCOM
2007
IEEE
16 years 23 days ago
Paradox of Shortest Path Routing for Large Multi-Hop Wireless Networks
— In this paper, we analyze the impact of straight line routing in large homogeneous multi-hop wireless networks. We estimate the nodal load, which is defined as the number of p...
Sungoh Kwon, Ness B. Shroff