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» A Fast Decision Tree Learning Algorithm
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JAIR
2010
145views more  JAIR 2010»
14 years 9 months ago
Fast Set Bounds Propagation Using a BDD-SAT Hybrid
Binary Decision Diagram (BDD) based set bounds propagation is a powerful approach to solving set-constraint satisfaction problems. However, prior BDD based techniques incur the si...
Graeme Gange, Peter J. Stuckey, Vitaly Lagoon
SBRN
2008
IEEE
15 years 5 months ago
Multi-label Text Categorization Using VG-RAM Weightless Neural Networks
In automated multi-label text categorization, an automatic categorization system should output a category set, whose size is unknown a priori, for each document under analysis. Ma...
Claudine Badue, Felipe Pedroni, Alberto Ferreira d...
IPPS
2010
IEEE
14 years 9 months ago
Offline library adaptation using automatically generated heuristics
Automatic tuning has emerged as a solution to provide high-performance libraries for fast changing, increasingly complex computer architectures. We distinguish offline adaptation (...
Frédéric de Mesmay, Yevgen Voronenko...
ICML
2000
IEEE
15 years 11 months ago
FeatureBoost: A Meta-Learning Algorithm that Improves Model Robustness
Most machine learning algorithms are lazy: they extract from the training set the minimum information needed to predict its labels. Unfortunately, this often leads to models that ...
Joseph O'Sullivan, John Langford, Rich Caruana, Av...
COLT
2001
Springer
15 years 3 months ago
On Using Extended Statistical Queries to Avoid Membership Queries
The Kushilevitz-Mansour (KM) algorithm is an algorithm that finds all the “large” Fourier coefficients of a Boolean function. It is the main tool for learning decision trees ...
Nader H. Bshouty, Vitaly Feldman