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192 514 (0,738s)

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On learning decomposable models.

Basic themes in document: graphical models; decomposable models; structural learning.

BD - Teorie informace

  • 2000
  • D
Result

Learning Decomposable Models for Classification.

Basic themes in document: learning; decomposable models; classification. ? ? ś î ô ö ú b...

JD - Využití počítačů, robotika a její aplikace

  • 2001
  • D
Result

Greedy search among decomposable models

Main topics of the document: Machine Learning; Greedy Search; Decomposable Models; Likelihood-ratio...

BA - Obecná matematika

  • 2011
  • D
  • Link
Result

Compositional Models: Iterative Structure Learning from Data

Main topics of the document: compositional models; structure learning; decomposability; Kullback-Leibler divergence...

Business and management

  • 2021
  • D
  • Link
Result

New Algorithm for Learning Decomposable Models.

Basic themes in document: graphical models; structure learning; bayesian networks.

BD - Teorie informace

  • 2000
  • D
Result

The chordal graph polytope for learning decomposable models

This theoretical paper is inspired by an integer linear programming (ILP) approach to learning the structure of decomposable models. We intend to represent decomposable models by special zero-one vectors...

BA - Obecná matematika

  • 2016
  • D
Result

Towards using the chordal graph polytope in learning decomposable models

The motivation for this paper is the integer linear programming (ILP) approach to learning the structure of a decomposable graphical model. We have chosen to represent decomposable models by means of speci...

Statistics and probability

  • 2017
  • Jimp
  • Link
Result

Entropy-Based Learning of Compositional Models from Data

We investigate learning of belief function compositional models from data using information content and mutual information based on two different definitions of entropy consistent and decomposable compositional model

Pure mathematics

  • 2021
  • D
  • Link
Result

An algeraic approach to structural learning Bayesian networks

Basic idea is that every Bayesian network (BN) model is uniquely described by a certain integral vector, named standard imset. Every score-equivalent decomposable criterion appreas to be an affine function of the standard imset. Alb...

BA - Obecná matematika

  • 2006
  • D
Result

Computing the Decomposable Entropy of Graphical Belief Function Models

the decomposable entropy of the model. Finally, the decomposable entropy generalizes Shannon’s-Shafer (D-S) belief functions called decomposable entropy. Here, we provide an algorithm for computing the decompo...

Applied mathematics

  • 2022
  • D
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