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» Learning with Kernels and Logical Representations
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ECML
2007
Springer
15 years 6 months ago
Probabilistic Explanation Based Learning
Abstract. Explanation based learning produces generalized explanations from examples. These explanations are typically built in a deductive manner and they aim to capture the essen...
Angelika Kimmig, Luc De Raedt, Hannu Toivonen
239
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NIPS
2008
15 years 1 months ago
Supervised Dictionary Learning
It is now well established that sparse signal models are well suited for restoration tasks and can be effectively learned from audio, image, and video data. Recent research has be...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
107
Voted
BCS
2008
15 years 1 months ago
A Customisable Multiprocessor for Application-Optimised Inductive Logic Programming
This paper describes a customisable processor designed to accelerate execution of inductive logic programming, targeting advanced field-programmable gate array (FPGA) technology. ...
Andreas Fidjeland, Wayne Luk, Stephen Muggleton
FLAIRS
2008
15 years 2 months ago
Toward Markov Logic with Conditional Probabilities
Combining probability and first-order logic has been the subject of intensive research during the last ten years. The most well-known formalisms combining probability and some sub...
Jens Fisseler
108
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IJCAI
2007
15 years 1 months ago
Recursive Random Fields
A formula in first-order logic can be viewed as a tree, with a logical connective at each node, and a knowledge base can be viewed as a tree whose root is a conjunction. Markov l...
Daniel Lowd, Pedro Domingos