187 search results - page 8 / 38 » Bounding the cost of learned rules |
CIAC
1994
Springer
13 years 11 months ago
1994
Springer
We consider the problem of maintaining a binary search tree (BST) that minimizes the average access cost needed to satisfy randomly generated requests. We analyze scenarios in whi...
NIPS
2004
13 years 8 months ago
2004
act out the core search problem of active learning schemes, to better understand the extent to which adaptive labeling can improve sample complexity. We give various upper and low...
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
Sampling is a popular way of scaling up machine learning algorithms to large datasets. The question often is how many samples are needed. Adaptive stopping algorithms monitor the ...
NAACL
2010
13 years 5 months ago
2010
We describe a method of incorporating taskspecific cost functions into standard conditional log-likelihood (CLL) training of linear structured prediction models. Recently introduc...
ICML
1999
IEEE
14 years 8 months ago
1999
IEEE
Lbr is a lazy semi-naive Bayesian classi er learning technique, designed to alleviate the attribute interdependence problem of naive Bayesian classi cation. To classify a test exa...