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188
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ICCV
2009
IEEE
15 years 4 months ago
2009
IEEE
The use of Mercer kernel methods in statistical learning theory provides for strong learning capabilities, as seen in kernel principal component analysis and support vector machin...
142
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OKCON
2011
14 years 9 months ago
2011
This paper describes a new theory of peer-to-peer learning and teaching that we call paragogy. Paragogy's principles were developed by adapting the Knowles's principles...
206
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KDD
2006
ACM
16 years 7 months ago
2006
ACM
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
186
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ICASSP
2008
IEEE
16 years 1 months ago
2008
IEEE
This paper investigates a class of learning problems called learning satisfiability (LSAT) problems, where the goal is to learn a set in the input (feature) space that satisfies...
188
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ATAL
2007
Springer
16 years 1 months ago
2007
Springer
Reinforcement learning is a popular and successful framework for many agent-related problems because only limited environmental feedback is necessary for learning. While many algo...