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» Active Learning with Model Selection in Linear Regression
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NAACL
2004
13 years 10 months ago
Ensemble-based Active Learning for Parse Selection
Supervised estimation methods are widely seen as being superior to semi and fully unsupervised methods. However, supervised methods crucially rely upon training sets that need to ...
Miles Osborne, Jason Baldridge
CDC
2009
IEEE
180views Control Systems» more  CDC 2009»
13 years 12 months ago
Robustness analysis for Least Squares kernel based regression: an optimization approach
—In kernel based regression techniques (such as Support Vector Machines or Least Squares Support Vector Machines) it is hard to analyze the influence of perturbed inputs on the ...
Tillmann Falck, Johan A. K. Suykens, Bart De Moor
IROS
2008
IEEE
191views Robotics» more  IROS 2008»
14 years 3 months ago
Local Gaussian process regression for real-time model-based robot control
— High performance and compliant robot control requires accurate dynamics models which cannot be obtained analytically for sufficiently complex robot systems. In such cases, mac...
Duy Nguyen-Tuong, Jan Peters
ECBS
2010
IEEE
230views Hardware» more  ECBS 2010»
13 years 12 months ago
A Model-Based Regression Testing Approach for Evolving Software Systems with Flexible Tool Support
Model-based selective regression testing promises reduction in cost and labour by selecting a subset of the test suite corresponding to the modifications after system evolution. H...
Qurat-ul-ann Farooq, Muhammad Zohaib Z. Iqbal, Zaf...
SEAL
1998
Springer
14 years 25 days ago
Genetic Programming with Active Data Selection
Genetic programming evolves Lisp-like programs rather than fixed size linear strings. This representational power combined with generality makes genetic programming an interesting ...
Byoung-Tak Zhang, Dong-Yeon Cho