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» Using Machine Learning to Guide Architecture Simulation
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ICML
2009
IEEE
14 years 2 months ago
Grammatical inference as a principal component analysis problem
One of the main problems in probabilistic grammatical inference consists in inferring a stochastic language, i.e. a probability distribution, in some class of probabilistic models...
Raphaël Bailly, François Denis, Liva R...
EWRL
2008
13 years 9 months ago
Optimistic Planning of Deterministic Systems
If one possesses a model of a controlled deterministic system, then from any state, one may consider the set of all possible reachable states starting from that state and using any...
Jean-François Hren, Rémi Munos
ML
2002
ACM
135views Machine Learning» more  ML 2002»
13 years 7 months ago
Bayesian Treed Models
When simple parametric models such as linear regression fail to adequately approximate a relationship across an entire set of data, an alternative may be to consider a partition o...
Hugh A. Chipman, Edward I. George, Robert E. McCul...
COLT
2010
Springer
13 years 6 months ago
Forest Density Estimation
We study graph estimation and density estimation in high dimensions, using a family of density estimators based on forest structured undirected graphical models. For density estim...
Anupam Gupta, John D. Lafferty, Han Liu, Larry A. ...
CN
2007
129views more  CN 2007»
13 years 8 months ago
Machine-learnt versus analytical models of TCP throughput
We first study the accuracy of two well-known analytical models of the average throughput of long-term TCP flows, namely the so-called SQRT and PFTK models, and show that these ...
Ibtissam El Khayat, Pierre Geurts, Guy Leduc