2914 search results - page 305 / 583 » Learning and Inference with Constraints |
215
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EMMCVPR
2011
Springer
14 years 6 months ago
2011
Springer
Traditional approaches to Multiple-Instance Learning (MIL) operate under the assumption that the instances of a bag are generated independently, and therefore typically learn an in...
178
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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...
151
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COLT
2005
Springer
16 years 6 days ago
2005
Springer
The paper deals with the following problem: is returning to wrong conjectures necessary to achieve full power of algorithmic learning? Returning to wrong conjectures complements t...
196
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KES
2005
Springer
16 years 5 days ago
2005
Springer
Much of the world’s data is in the form of time series, and many other types of data, such as video, image, and handwriting, can easily be transformed into time series. This fact...
174
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WAPCV
2004
Springer
16 years 6 hour ago
2004
Springer
Abstract. Selective attention shift can help neural networks learn invariance. We describe a method that can produce a network with invariance to changes in visual input caused by ...