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» Input Modeling Using Quantile Statistical Methods
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ICML
2010
IEEE
15 years 7 months ago
Learning the Linear Dynamical System with ASOS
We develop a new algorithm, based on EM, for learning the Linear Dynamical System model. Called the method of Approximated Second-Order Statistics (ASOS) our approach achieves dra...
James Martens
DPHOTO
2009
126views Hardware» more  DPHOTO 2009»
15 years 4 months ago
Measuring texture sharpness of a digital camera
A method for evaluating texture quality as shot by a camera is presented. It is shown that usual sharpness measurements are not completely satisfying for this task. A new target b...
Frédéric Cao, Frederic Guichard, Her...
SMA
2006
ACM
225views Solid Modeling» more  SMA 2006»
16 years 17 days ago
Feature sensitive mesh segmentation
Segmenting meshes into natural regions is useful for model understanding and many practical applications. In this paper, we present a novel, automatic algorithm for segmenting me...
Yu-Kun Lai, Qian-Yi Zhou, Shi-Min Hu, Ralph R. Mar...
IDA
2010
Springer
15 years 8 months ago
Oracle Coached Decision Trees and Lists
This paper introduces a novel method for obtaining increased predictive performance from transparent models in situations where production input vectors are available when building...
Ulf Johansson, Cecilia Sönströd, Tuve L&...
KDD
2007
ACM
148views Data Mining» more  KDD 2007»
16 years 7 months ago
Scalable look-ahead linear regression trees
Most decision tree algorithms base their splitting decisions on a piecewise constant model. Often these splitting algorithms are extrapolated to trees with non-constant models at ...
David S. Vogel, Ognian Asparouhov, Tobias Scheffer