DSN
2011
IEEE
12 years 4 months ago
2011
IEEE
—In this paper we extend the class of MAP queueing networks to include blocking models, which are useful to describe the performance of service instances which have a limited con...
TCOM
2010
12 years 11 months ago
2010
In order to provide a concise time-varying SISO channel model, the principle of maximum entropy is applied to scattering function derivation. The resulting model is driven by few p...
CORR
2010
Springer
13 years 1 months ago
2010
Springer
Describing the collective activity of neural populations is a daunting task: the number of possible patterns grows exponentially with the number of cells, resulting in practically...
KAIS
2008
13 years 4 months ago
2008
We consider the problem of defining the significance of an itemset. We say that the itemset is significant if we are surprised by its frequency when compared to the frequencies of ...
ICML
2010
IEEE
13 years 5 months ago
2010
IEEE
The principle of maximum entropy provides a powerful framework for statistical models of joint, conditional, and marginal distributions. However, there are many important distribu...
UAI
2000
13 years 5 months ago
2000
We give an interpretation of the Maximum Entropy (MaxEnt) Principle in gametheoretic terms. Based on this interpretation, we make a formal distinction between di erent ways of app...
ACL
1998
13 years 5 months ago
1998
Maximum entropy framework proved to be expressive and powerful for the statistical language modelling, but it suffers from the computational expensiveness of the model building. T...
UAI
2004
13 years 5 months ago
2004
Exponential models of distributions are widely used in machine learning for classification and modelling. It is well known that they can be interpreted as maximum entropy models u...
NIPS
2004
13 years 5 months ago
2004
We establish a mistake bound for an ensemble method for classification based on maximizing the entropy of voting weights subject to margin constraints. The bound is the same as a ...
TRECVID
2008
13 years 5 months ago
2008
Run No. Run ID Run Description infMAP (%) training on TV08 data 1 IUPR-TV-M SIFT visual words with maximum entropy 6.1 2 IUPR-TV-MF SIFT with maximum entropy, fused with color+tex...