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DATAMINE
2002
125views more  DATAMINE 2002»
15 years 3 months ago
High-Performance Commercial Data Mining: A Multistrategy Machine Learning Application
We present an application of inductive concept learning and interactive visualization techniques to a large-scale commercial data mining project. This paper focuses on design and c...
William H. Hsu, Michael Welge, Thomas Redman, Davi...
PLDI
2009
ACM
15 years 10 months ago
PetaBricks: a language and compiler for algorithmic choice
It is often impossible to obtain a one-size-fits-all solution for high performance algorithms when considering different choices for data distributions, parallelism, transformati...
Jason Ansel, Cy P. Chan, Yee Lok Wong, Marek Olsze...
ICML
1999
IEEE
16 years 4 months ago
Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes
We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
Sebastian Thrun, John Langford, Dieter Fox
ML
2000
ACM
154views Machine Learning» more  ML 2000»
15 years 2 months ago
Lazy Learning of Bayesian Rules
The naive Bayesian classifier provides a simple and effective approach to classifier learning, but its attribute independence assumption is often violated in the real world. A numb...
Zijian Zheng, Geoffrey I. Webb
ICASSP
2011
IEEE
14 years 7 months ago
Marker-based Hierarchical Segmentation and classification approach for hyperspectral imagery
The Hierarchical SEGmentation (HSEG) algorithm, which is a combination of hierarchical step-wise optimization and spectral clustering, has given good performances for hyperspectra...
Yuliya Tarabalka, James C. Tilton, Jon Atli Benedi...