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» Learning Bounds for Domain Adaptation
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FCT
2009
Springer
15 years 7 months ago
Competitive Group Testing and Learning Hidden Vertex Covers with Minimum Adaptivity
Suppose that we are given a set of n elements d of which are “defective”. A group test can check for any subset, called a pool, whether it contains a defective. It is well know...
Peter Damaschke, Azam Sheikh Muhammad
112
Voted
EXPERT
2008
134views more  EXPERT 2008»
15 years 16 days ago
Learning to Tag and Tagging to Learn: A Case Study on Wikipedia
Natural language technologies have been long envisioned to play a crucial role in transitioning from the current Web to a more "semantic" Web. If anything, the significa...
Peter Mika, Massimiliano Ciaramita, Hugo Zaragoza,...
CODCRY
2009
Springer
111views Cryptology» more  CODCRY 2009»
15 years 7 months ago
On the Impossibility of Strong Encryption Over
We give two impossibility results regarding strong encryption over an infinite enumerable domain. The first one relates to statistically secure one-time encryption. The second on...
Raphael C.-W. Phan, Serge Vaudenay
NIPS
1998
15 years 1 months ago
Dynamically Adapting Kernels in Support Vector Machines
The kernel-parameter is one of the few tunable parameters in Support Vector machines, controlling the complexity of the resulting hypothesis. Its choice amounts to model selection...
Nello Cristianini, Colin Campbell, John Shawe-Tayl...
ICEIS
2009
IEEE
15 years 7 months ago
CrimsonHex: A Service Oriented Repository of Specialised Learning Objects
The corner stone of the interoperability of eLearning systems is the standard definition of learning objects. Nevertheless, for some domains this standard is insufficient to fully ...
José Paulo Leal, Ricardo Queirós