399 search results - page 67 / 80 » Robust Boosting for Learning from Few Examples |
122
Voted
JMLR
2012
13 years 2 months ago
2012
We study the prevalent problem when a test distribution differs from the training distribution. We consider a setting where our training set consists of a small number of sample d...
102
Voted
ML
2010
ACM
14 years 6 months ago
2010
ACM
Traditional classification methods assume that the training and the test data arise from the same underlying distribution. However, in several adversarial settings, the test set is...
122
Voted
KDD
2007
ACM
16 years 2 days ago
2007
ACM
It is becoming increasingly common to construct databases from information automatically culled from many heterogeneous sources. For example, a research publication database can b...
115
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CVPR
2004
IEEE
16 years 1 months ago
2004
IEEE
We propose a new Bayesian approach to object-based image retrieval with relevance feedback. Although estimating the object posterior probability density from few examples seems in...
TIP
2008
14 years 11 months ago
2008
Previous research applying kernel methods such as support vector machines (SVMs) to hyperspectral image classification has achieved performance competitive with the best available ...