1174 search results - page 24 / 235 » Boosting for transfer learning |
ECML
2007
Springer
15 years 4 months ago
2007
Springer
Boosting is a simple yet powerful modeling technique that is used in many machine learning and data mining related applications. In this paper, we propose a novel scale-space based...
CIKM
2000
Springer
15 years 2 months ago
2000
Springer
RankBoost is a recently proposed algorithm for learning ranking functions. It is simple to implement and has strong justifications from computational learning theory. We describe...
VR
2008
IEEE
14 years 9 months ago
2008
IEEE
: The aim of all education is to apply what we learn in different contexts and to recognise and extend this learning to new situations. Virtual learning environments can used to bu...
ICML
2003
IEEE
15 years 10 months ago
2003
IEEE
The paper extends the notion of linear programming boosting to handle uneven datasets. Extensive experiments with text classification problem compare the performance of a number o...
AAAI
2007
15 years 3 days ago
2007
Transfer learning addresses the problem of how to leverage knowledge acquired in a source domain to improve the accuracy and speed of learning in a related target domain. This pap...