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EDM
2009
116views Data Mining» more  EDM 2009»
13 years 5 months ago
Determining the Significance of Item Order In Randomized Problem Sets
Researchers who make tutoring systems would like to know which sequences of educational content lead to the most effective learning by their students. The majority of data collecte...
Zachary A. Pardos, Neil T. Heffernan
PKDD
2007
Springer
121views Data Mining» more  PKDD 2007»
14 years 1 months ago
Improved Algorithms for Univariate Discretization of Continuous Features
In discretization of a continuous variable its numerical value range is divided into a few intervals that are used in classification. For example, Na¨ıve Bayes can benefit from...
Jussi Kujala, Tapio Elomaa
ML
2002
ACM
128views Machine Learning» more  ML 2002»
13 years 7 months ago
A Simple Method for Generating Additive Clustering Models with Limited Complexity
Additive clustering was originally developed within cognitive psychology to enable the development of featural models of human mental representation. The representational flexibili...
Michael D. Lee
UAI
2003
13 years 9 months ago
Bayesian Hierarchical Mixtures of Experts
The Hierarchical Mixture of Experts (HME) is a well-known tree-structured model for regression and classification, based on soft probabilistic splits of the input space. In its o...
Christopher M. Bishop, Markus Svensén
SIAMSC
2010
141views more  SIAMSC 2010»
13 years 6 months ago
An Iterative Method for Edge-Preserving MAP Estimation When Data-Noise Is Poisson
In numerous applications of image processing, e.g. astronomical and medical imaging, data-noise is well-modeled by a Poisson distribution. This motivates the use of the negative-lo...
Johnathan M. Bardsley, John Goldes