2363 search results - page 28 / 473 » Learning Algorithms for Domain Adaptation |
EMNLP
2009
13 years 5 months ago
2009
Bootstrapping is the process of improving the performance of a trained classifier by iteratively adding data that is labeled by the classifier itself to the training set, and retr...
ECAI
2010
Springer
13 years 8 months ago
2010
Springer
We investigate the problem of learning action effects in partially observable STRIPS planning domains. Our approach is based on a voted kernel perceptron learning model, where act...
ESANN
2004
13 years 9 months ago
2004
In this paper we propose an Rprop modification that builds on a mathematical framework for the convergence analysis to equip Rprop with a learning rates adaptation strategy that en...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
Link prediction is a key technique in many applications such as recommender systems, where potential links between users and items need to be predicted. A challenge in link predic...
KR
2004
Springer
14 years 27 days ago
2004
Springer
To learn to behave in highly complex domains, agents must represent and learn compact models of the world dynamics. In this paper, we present an algorithm for learning probabilist...