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» On the Complexity of Function Learning
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BMCBI
2006
118views more  BMCBI 2006»
15 years 1 months ago
Predicting the effect of missense mutations on protein function: analysis with Bayesian networks
Background: A number of methods that use both protein structural and evolutionary information are available to predict the functional consequences of missense mutations. However, ...
Chris J. Needham, James R. Bradford, Andrew J. Bul...
71
Voted
HCI
2009
14 years 11 months ago
Combining Electroencephalograph and Functional Near Infrared Spectroscopy to Explore Users' Mental Workload
We discuss the physiological metrics that can be measured with electroencephalography (EEG) and functional near infrared spectroscopy (fNIRs). We address the functional and practic...
Leanne M. Hirshfield, Krysta Chauncey, Rebecca Gul...
141
Voted
ICCV
2009
IEEE
14 years 11 months ago
Image annotation using multi-label correlated Green's function
Image annotation has been an active research topic in the recent years due to its potentially large impact on both image understanding and web/database image search. In this paper...
Hua Wang, Heng Huang, Chris H. Q. Ding
ICANN
2005
Springer
15 years 6 months ago
Interpolation Mechanism of Functional Networks
In this paper, the interpolation mechanism of functional networks is discussed. A kind of fourlayer (with 1 input and 1 output unit) and a five-layer (with double input and single...
Yong-Quan Zhou, Licheng Jiao
102
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CORR
2010
Springer
116views Education» more  CORR 2010»
15 years 1 months ago
Multi-View Active Learning in the Non-Realizable Case
The sample complexity of active learning under the realizability assumption has been well-studied. The realizability assumption, however, rarely holds in practice. In this paper, ...
Wei Wang, Zhi-Hua Zhou