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» A Boosting Algorithm for Regression
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99
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ICDM
2009
IEEE
137views Data Mining» more  ICDM 2009»
15 years 9 months ago
Regression Learning Vector Quantization
— Learning Vector Quantization (LVQ) is a popular class of nearest prototype classifiers for multiclass classification. Learning algorithms from this family are widely used becau...
Mihajlo Grbovic, Slobodan Vucetic
ISSTA
1998
ACM
15 years 6 months ago
On the Limit of Control Flow Analysis for Regression Test Selection
Automated analyses for regression test selection (RTS) attempt to determine if a modified program, when run on a test t, will have the same behavior as an old version of the prog...
Thomas Ball
117
Voted
IJCAI
2007
15 years 4 months ago
Probabilistic Consistency Boosts MAC and SAC
Constraint Satisfaction Problems (CSPs) are ubiquitous in Artificial Intelligence. The backtrack algorithms that maintain some local consistency during search have become the de ...
Deepak Mehta, Marc R. C. van Dongen
ICML
2005
IEEE
16 years 3 months ago
Combining model-based and instance-based learning for first order regression
T ORDER REGRESSION (EXTENDED ABSTRACT) Kurt Driessensa Saso Dzeroskib a Department of Computer Science, University of Waikato, Hamilton, New Zealand (kurtd@waikato.ac.nz) b Departm...
Kurt Driessens, Saso Dzeroski
113
Voted
ICML
2003
IEEE
16 years 3 months ago
Relational Instance Based Regression for Relational Reinforcement Learning
Relational reinforcement learning (RRL) is a Q-learning technique which uses first order regression techniques to generalize the Qfunction. Both the relational setting and the Q-l...
Kurt Driessens, Jan Ramon