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» Post-Analysis of Learned Rules
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ICANN
2003
Springer
15 years 9 months ago
Optimal Hebbian Learning: A Probabilistic Point of View
Many activity dependent learning rules have been proposed in order to model long-term potentiation (LTP). Our aim is to derive a spike time dependent learning rule from a probabili...
Jean-Pascal Pfister, David Barber, Wulfram Gerstne...
ICML
1997
IEEE
16 years 4 months ago
Automatic Rule Acquisition for Spelling Correction
This paper describes a new approach to automatically learning linguistic knowledge for spelling correction. A major feature of this approach is the fact that the acquired knowledg...
Lidia Mangu, Eric Brill
159
Voted
ICMLA
2009
15 years 1 months ago
Learning Parameters for Relational Probabilistic Models with Noisy-Or Combining Rule
Languages that combine predicate logic with probabilities are needed to succinctly represent knowledge in many real-world domains. We consider a formalism based on universally qua...
Sriraam Natarajan, Prasad Tadepalli, Gautam Kunapu...
ECML
2001
Springer
15 years 8 months ago
A Framework for Learning Rules from Multiple Instance Data
Abstract. This paper proposes a generic extension to propositional rule learners to handle multiple-instance data. In a multiple-instance representation, each learning example is r...
Yann Chevaleyre, Jean-Daniel Zucker
126
Voted
ICML
2001
IEEE
16 years 4 months ago
Round Robin Rule Learning
In this paper, we discuss a technique for handling multi-class problems with binary classifiers, namely to learn one classifier for each pair of classes. Although this idea is kno...
Johannes Fürnkranz