136 search results - page 21 / 28 » On Learning Monotone Boolean Functions |
ICANN
2007
Springer
15 years 4 months ago
2007
Springer
Finding the largest linearly separable set of examples for a given Boolean function is a NP-hard problem, that is relevant to neural network learning algorithms and to several prob...
PAMI
2006
14 years 9 months ago
2006
Gaussian process classifiers (GPCs) are Bayesian probabilistic kernel classifiers. In GPCs, the probability of belonging to a certain class at an input location is monotonically re...
DAGM
2004
Springer
15 years 3 months ago
2004
Springer
We present an approach to discretizing multivariate continuous data while learning the structure of a graphical model. We derive the joint scoring function from the principle of p...
ICML
2004
IEEE
15 years 10 months ago
2004
IEEE
This paper extends previous work on the Skewing algorithm, a promising approach that allows greedy decision tree induction algorithms to handle problematic functions such as parit...
ECML
2006
Springer
15 years 1 months ago
2006
Springer
Causal independence modelling is a well-known method both for reducing the size of probability tables and for explaining the underlying mechanisms in Bayesian networks. In this pap...