1455 search results - page 130 / 291 » Exploiting Myopic Learning |
151
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KDD
2010
ACM
15 years 6 months ago
2010
ACM
Active learning (AL) is an increasingly popular strategy for mitigating the amount of labeled data required to train classifiers, thereby reducing annotator effort. We describe ...
148
Voted
CIKM
2008
Springer
15 years 6 months ago
2008
Springer
Learning-to-rank algorithms, which can automatically adapt ranking functions in web search, require a large volume of training data. A traditional way of generating training examp...
155
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FGCS
2006
15 years 4 months ago
2006
CSCL systems can benefit from using grids since they offer a common infrastructure enabling the access to an extended pool of resources that can provide supercomputing capabilitie...
147
Voted
PKDD
2010
Springer
15 years 2 months ago
2010
Springer
Abstract. One solution to the lack of label problem is to exploit transfer learning, whereby one acquires knowledge from source-domains to improve the learning performance in the t...
171
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JMLR
2011
14 years 11 months ago
2011
While most supervised machine learning models assume that training examples are sampled at random or adversarially, this article is concerned with models of learning from a cooper...