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» Marginals of DAG-Isomorphic Independence Models
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JMLR
2008
141views more  JMLR 2008»
13 years 7 months ago
Graphical Methods for Efficient Likelihood Inference in Gaussian Covariance Models
In graphical modelling, a bi-directed graph encodes marginal independences among random variables that are identified with the vertices of the graph. We show how to transform a bi...
Mathias Drton, Thomas S. Richardson
WSC
2007
13 years 9 months ago
A method for fast generation of bivariate Poisson random vectors
It is well known that trivariate reduction — a method to generate two dependent random variables from three independent random variables — can be used to generate Poisson rand...
Kaeyoung Shin, Raghu Pasupathy
JMLR
2011
145views more  JMLR 2011»
13 years 2 months ago
Cumulative Distribution Networks and the Derivative-sum-product Algorithm: Models and Inference for Cumulative Distribution Func
We present a class of graphical models for directly representing the joint cumulative distribution function (CDF) of many random variables, called cumulative distribution networks...
Jim C. Huang, Brendan J. Frey
WINE
2007
Springer
126views Economy» more  WINE 2007»
14 years 1 months ago
A Theory of Loss-Leaders: Making Money by Pricing Below Cost
We consider the problem of assigning prices to goods of fixed marginal cost in order to maximize revenue in the presence of single-minded customers. We focus in particular on the...
Maria-Florina Balcan, Avrim Blum, T.-H. Hubert Cha...
JMLR
2006
120views more  JMLR 2006»
13 years 7 months ago
Kernel-Based Learning of Hierarchical Multilabel Classification Models
We present a kernel-based algorithm for hierarchical text classification where the documents are allowed to belong to more than one category at a time. The classification model is...
Juho Rousu, Craig Saunders, Sándor Szedm&aa...