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» Using minimum description length for process mining
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DAGM
2005
Springer
14 years 2 months ago
Agglomerative Grouping of Observations by Bounding Entropy Variation
Abstract. An information theoretic framework for grouping observations is proposed. The entropy change incurred by new observations is analyzed using the Kalman filter update equa...
Christian Beder
EMNLP
2009
13 years 6 months ago
First- and Second-Order Expectation Semirings with Applications to Minimum-Risk Training on Translation Forests
Many statistical translation models can be regarded as weighted logical deduction. Under this paradigm, we use weights from the expectation semiring (Eisner, 2002), to compute fir...
Zhifei Li, Jason Eisner
KDD
1995
ACM
176views Data Mining» more  KDD 1995»
14 years 15 days ago
MDL-Based Decision Tree Pruning
This paper explores the application of the Minimum Description Length principle for pruning decision trees. We present a new algorithm that intuitively captures the primary goal o...
Manish Mehta 0002, Jorma Rissanen, Rakesh Agrawal
KDD
2004
ACM
198views Data Mining» more  KDD 2004»
14 years 2 months ago
Mining traffic data from probe-car system for travel time prediction
We are developing a technique to predict travel time of a vehicle for an objective road section, based on real time traffic data collected through a probe-car system. In the area ...
Takayuki Nakata, Jun-ichi Takeuchi
ICASSP
2011
IEEE
13 years 20 days ago
Sparse coding and dictionary learning based on the MDL principle
The power of sparse signal coding with learned overcomplete dictionaries has been demonstrated in a variety of applications and fields, from signal processing to statistical infe...
Ignacio Ramírez, Guillermo Sapiro