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» Learning on the Test Data: Leveraging Unseen Features
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ICML
2003
IEEE
14 years 5 months ago
Learning on the Test Data: Leveraging Unseen Features
This paper addresses the problem of classification in situations where the data distribution is not homogeneous: Data instances might come from different locations or times, and t...
Benjamin Taskar, Ming Fai Wong, Daphne Koller
ECCV
2010
Springer
13 years 9 months ago
Learning to Recognize Objects from Unseen Modalities
Abstract. In this paper we investigate the problem of exploiting multiple sources of information for object recognition tasks when additional modalities that are not present in the...
CSB
2005
IEEE
166views Bioinformatics» more  CSB 2005»
13 years 10 months ago
Artificial Neural Networks to Predict Daylily Hybrids
Artificial Neural Networks (ANN) were employed to predict daylily (Hemerocalli spp.) hybrids from known characteristics of parents used in hybridization. Features such as height, ...
Ramana M. Gosukonda, Masoud Naghedolfeizi, Johnny ...
JMLR
2010
104views more  JMLR 2010»
12 years 12 months ago
How to Explain Individual Classification Decisions
After building a classifier with modern tools of machine learning we typically have a black box at hand that is able to predict well for unseen data. Thus, we get an answer to the...
David Baehrens, Timon Schroeter, Stefan Harmeling,...
JMLR
2010
100views more  JMLR 2010»
12 years 12 months ago
Parametric Herding
A parametric version of herding is formulated. The nonlinear mapping between consecutive time slices is learned by a form of self-supervised training. The resulting dynamical syst...
Yutian Chen, Max Welling