Minimum Description Length Principle
Filtering Spams using the Minimum Description Length Principle
... In this paper, we present a novel anti-spam classifier based on the minimum description length principle [4]. We con- ducted an empirical experiment using six well-known, large and public ...
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Maintaining regularity and generalizationin data using the minimum description length principle and genetic algorithm: case of grammatical inference
... the minimum description length principle, but is limited to positive examples ...the minimum description length ...
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CiteSeerX — Model Selection and the Principle of Minimum Description Length
... This paper reviews the principle of Minimum Description Length (MDL) for problems of model selection. By viewing statistical modeling as a means of generating descriptions of observed data, ...
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The minimum description length principle
... the minimum de- scription length (MDL) principle and the related theory of stochastic com- ...MDL principle seeks to place the age-old statistical or induc- tive inference on a sound ...the ...
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MoL 2007 03: Transfer Learning Using the Minimum Description Length Principle with a Decision Tree Application
... part description length minimization better then weighing the prior knowledge? A proof that our approach is better or not then the three part MDL approach would be nice, but that is the subject of another ...
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Inference of Phrase Based Translation Models via Minimum Description Length
... Universitat Polit`ecnica de Val`encia, Camino de Vera s/n, 46021 Valencia (Spain) {jegonzalez, fcn}@dsic.upv.es Abstract We present an unsupervised inference pro- cedure for phrase-based translation mod- els based on the ...
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Using Minimum Description Length for Discretization Classification of Data Modeled by Bayesian Networks
... 4 Minimum Description Length For Discretization Friedman and Goldszmidt [10] have developed a method for discretization of continuous data for Bayesian networks which is based on the minimum ...
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Minimum Description Length Revisited
... MDL Principle without resorting to information theory: all the material can be understood without any knowledge of data compression, which should make it a much easier read for statisticians and machine learn- ing ...
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Minimum Description Length Model Selection - Problems and Extensions
... MDL Principle for Model Selection Suppose we consider a number of different hypotheses for some ...The Minimum Description Length (MDL) principle is such a criterion [67, ...literal ...
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Minimum Conditional Description Length Estimation for Markov Random Fields
... The Minimum Description Length (MDL) [18] principle states essentially that the best model is that one that provides the best compression of the ...
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Regularity Normalization: Constraining Implicit Space with Minimum Description Length
... MDL principle and proposed to consider neural network training process as a model selection ...code length by normalized maximum likelihood in an incremental fashion, and showed this imple- mentation can be ...
Unsupervised Transduction Grammar Induction via Minimum Description Length
... We present a minimalist, unsupervised learning model that induces relatively clean phrasal inversion transduction gram- mars by employing the minimum descrip- tion length principle to drive search ...
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Minimum Description Length Methods in Bayesian Model Selection: Some Applications
... introduced by [4] which do not seem to be in the spirit of the Bayesian approach that we have taken here. The discussion below is organized as follows. In Sec- tion 2 we briefly describe the MDL principle and then ...
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Minimum Description Length Penalization for Group and Multi-Task Sparse Learning
... We propose a framework MIC (Multiple Inclusion Criterion) for learning sparse models based on the information theoretic Minimum Description Length (MDL) principle. MIC provides an elegant way ...
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Text Segmentation by Language Using Minimum Description Length
... Kyushu University [email protected] Abstract The problem addressed in this paper is to seg- ment a given multilingual document into seg- ments for each language and then identify the language of each segment. The ...
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Minimum description length neural networks for time series prediction
... We cannot prove that this algorithm will work best for any given data set. For any particular data set we actually expect this algorithm to be sub-optimal. However, theory shows that the functional form 共7兲 is adequate ...
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Bayesian Minimum Description Length Techniques for Multiple Changepoint Detection
... Our motivation lies in climatology. Here, a metadata record, which is a file listing times when a recording station physically moved, instrumentation was changed, etc., sometimes exists. While metadata records are ...
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Minimum Description Length and the Inference of Scene Structure from Images
... [7] S.J. Maybank and R. Fraile, \Minimum description length method for facet matching," Proc. Interna- tional Symposium on Multispectral Image Processing, ISMIP'98, SPIE Vol. 3545, Wuhan, China, ...
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Efficient Unsupervised Recursive Word Segmentation Using Minimum Description Length
... of description length (DL) for word segmentation enables an efficient algorithm (based on pattern-matching methods) for greedy morpho- logical segmentation of the ...
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Minimum description length quality measurues for modular functional network architectures
... Universidad Nacional de la Patagonia Austral, R´ ıo Gallegos, Argentina Abstract Modular neural networks (MNNs) are increasingly popular models for dealing with complex problems constituted by a number of dependent ...
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