Minimum-Description Length Methods
Minimum Description Length Methods in Bayesian Model Selection: Some Applications
... Computations involved in Bayesian approach to practical model selection problems are usually very difficult. Computa- tional simplifications are sometimes possible, but are not generally applicable. There is a large ...
15
Minimum Description Length Revisited
... History of the Field, Recent Advances and Overview of this Paper MDL was introduced in 1978 by Jorma Rissanen in his paper Modeling by the Shortest Data Description. The paper coined the term MDL and introduced ...
38
The minimum description length principle
... Another application of universal-model based MDL is the type of prob- lem usually studied in statistical learning theory (Vapnik 1998); see also Chap- ter 17, Section 17.10. Here the goal is to directly learn functions ...
63
Text Segmentation by Language Using Minimum Description Length
... Previous work that directly concerns the problem addressed in this paper is rare. The most similar previous work that we know of comes from two sources and can be summarized as follows. First, (Teahan, 2000) attempted to ...
10
Filtering Spams using the Minimum Description Length Principle
... MDL methods is that they provide automatically and inherently protect against overfitting and can be used to estimate both the parameters and the structure of a ...traditional methods such as maximum ...
5
Regularity Normalization: Constraining Implicit Space with Minimum Description Length
... Preliminary results offered a proof of concept to the pro- posed method. Given the limited experiments at the current state, our approach empirically outperforms existing normal- ization methods its advantage in ...
Bayesian Minimum Description Length Techniques for Multiple Changepoint Detection
... The methods are illustrated in the analysis of 114 years of monthly temperatures from Tuscaloosa, ...the methods allow maximum and minimum temperatures to be jointly ...
102
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 ...
7
Minimum Description Length Penalization for Group and Multi-Task Sparse Learning
... theoretic Minimum Description Length (MDL) ...three methods are designed for selecting a small set of predictive features from a large pool of candidate ...
40
Minimum description length quality measurues for modular functional network architectures
... Minimun Description Length for Model Selection The problem of model selection has been extensively analyzed from several points of view ...proposed methods, the Minimum Description ...
12
Using Minimum Description Length for Discretization Classification of Data Modeled by Bayesian Networks
... 2.2.3 Priors for the Multinomial Network The terminology Bayesian network derives from the application of Bayes rule in order to determine certain conditional probabilities. A study using Bayesian networks does not ...
70
Maintaining regularity and generalizationin data using the minimum description length principle and genetic algorithm: case of grammatical inference
... Also, it is important to note that the Boolean based operators introduce the diversity in the population in a generative manner that helps the proposed GAWMDL to alleviate the premature convergence. The performance of ...
14
CiteSeerX — Model Selection and the Principle of Minimum Description Length
... in the nal expression for code length. A proof of this somewhat surprising equivalence between predictive and mixture code lengths can be found, for example, in Yu and Speed (1992) for a general multinomial model. ...
52
Minimum Description Length Model Selection - Problems and Extensions
... The Minimum Description Length (MDL) principle is such a criterion [67, ...the length of the encoded representation of the data can be expressed in ...
226
Minimum Conditional Description Length Estimation for Markov Random Fields
... VI. D ISCUSSION In this paper we have elaborated on the concept inherent in Maximum Pseudo-Likelihood, namely, that of using con- ditioning to simplify the task of parameter estimation, and have posed the problem as one ...
6
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 ...
12
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 over a ...
7
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, ...
7
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 ...
5
Segmenting vs. Chunking Rules: Unsupervised ITG Induction via Minimum Conditional Description Length
... the minimum con- ditional description length (MCDL) objective to drive the search for phrasal rules simultaneously from the two opposing types of ITG constraints, both of which have individually been ...
9