297 search results - page 12 / 60 » Learning from Ambiguously Labeled Examples |
ICML
2001
IEEE
14 years 11 months ago
2001
IEEE
Data noise is present in many machine learning problems domains, some of these are well studied but others have received less attention. In this paper we propose an algorithm for ...
ICML
2007
IEEE
14 years 11 months ago
2007
IEEE
Multi-instance learning and semi-supervised learning are different branches of machine learning. The former attempts to learn from a training set consists of labeled bags each con...
ICML
2005
IEEE
14 years 11 months ago
2005
IEEE
Due to its occurrence in engineering domains and implications for natural learning, the problem of utilizing unlabeled data is attracting increasing attention in machine learning....
KDD
2009
ACM
14 years 11 months ago
2009
ACM
This paper addresses Named Entity Mining (NEM), in which we mine knowledge about named entities such as movies, games, and books from a huge amount of data. NEM is potentially use...
ICML
2002
IEEE
14 years 11 months ago
2002
IEEE
Supervised learning techniques for text classi cation often require a large number of labeled examples to learn accurately. One way to reduce the amountoflabeled datarequired is t...