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Found 3 papers, 1 papers with code
Efficient learning of large sets of locally optimal classification rules
Instead, we propose an efficient algorithm that aims at finding the best rule covering each training example in a greedy optimization consisting of one specialization and one generalization loop.
An Empirical Investigation into Deep and Shallow Rule Learning
Inductive rule learning is arguably among the most traditional paradigms in machine learning.
An Investigation into Mini-Batch Rule Learning
We investigate whether it is possible to learn rule sets efficiently in a network structure with a single hidden layer using iterative refinements over mini-batches of examples.
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