@article{Golea1996OnL, title={On learning ?-perceptron networks on the uniform distribution}, author={Mostefa Golea and Mario Marchand and Thomas R. Hancock}, journal={Neural Networks}, year={1996}, volume={9}, pages={67-82} }

- Published 1996 in Neural Networks
DOI:10.1016/0893-6080(95)00009-7

We investigate the learnability, under the uniform distribution, of neural concepts that can be represented as simple combinations of nonoverlapping perceptrons (also called μ perceptrons) with binary weights and arbitrary thresholds. Two perceptrons are said to be nonoverlapping if they do not share any input variables. Specifically, we investigate, within the distribution-specific PAC model, the learnability of μ perceptron unions, decision lists , and generalized decision lists . In contrast… CONTINUE READING