1339 search results - page 4 / 268 » Learning Functions from Imperfect Positive Data |
ICANN
2009
Springer
14 years 2 days ago
2009
Springer
This paper proposes a modelling of Support Vector Machine (SVM) learning to address the problem of learning with sloppy labels. In binary classification, learning with sloppy labe...
KDD
2008
ACM
14 years 7 months ago
2008
ACM
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
ALT
2004
Springer
14 years 4 months ago
2004
Springer
In this paper we introduce a paradigm for learning in the limit of potentially infinite languages from all positive data and negative counterexamples provided in response to the ...
ECML
2005
Springer
14 years 1 months ago
2005
Springer
Abstract. We study the problem of learning from positive and unlabeled examples. Although several techniques exist for dealing with this problem, they all assume that positive exam...
ICGI
2010
Springer
13 years 8 months ago
2010
Springer
This paper presents an efficient algorithm that identifies a rich subclass of multiple context-free languages in the limit from positive data and membership queries by observing wh...