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» Using minimum description length for process mining
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IJCAI
1993
13 years 10 months ago
Multi-Interval Discretization of Continuous-Valued Attributes for Classification Learning
Since most real-world applications of classification learning involve continuous-valued attributes, properly addressing the discretization process is an important problem. This pa...
Usama M. Fayyad, Keki B. Irani
ICIP
2001
IEEE
14 years 10 months ago
Coding theoretic approach to image segmentation
This paper introduces multi-scale tree-based approaches to image segmentation, using Rissanen's coding theoretic minimum description length (MDL) principle to penalize overly...
Mário A. T. Figueiredo, Robert D. Nowak, Un...
MICCAI
2005
Springer
14 years 9 months ago
Nonrigid Shape Correspondence Using Landmark Sliding, Insertion and Deletion
The growing usage of statistical shape analysis in medical imaging calls for effective methods for highly accurate shape correspondence. This paper presents a novel landmark-based ...
Theodor Richardson, Song Wang
EDBT
2009
ACM
138views Database» more  EDBT 2009»
14 years 3 months ago
FOGGER: an algorithm for graph generator discovery
To our best knowledge, all existing graph pattern mining algorithms can only mine either closed, maximal or the complete set of frequent subgraphs instead of graph generators whic...
Zhiping Zeng, Jianyong Wang, Jun Zhang, Lizhu Zhou
COLT
2004
Springer
14 years 2 months ago
Convergence of Discrete MDL for Sequential Prediction
We study the properties of the Minimum Description Length principle for sequence prediction, considering a two-part MDL estimator which is chosen from a countable class of models....
Jan Poland, Marcus Hutter