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A note on sample complexity of learning binary output neural networks
  under fixed input distributions

A note on sample complexity of learning binary output neural networks under fixed input distributions

8 July 2010
V. Pestov
ArXiv (abs)PDFHTML

Papers citing "A note on sample complexity of learning binary output neural networks under fixed input distributions"

2 / 2 papers shown
PAC learnability under non-atomic measures: a problem by Vidyasagar
PAC learnability under non-atomic measures: a problem by VidyasagarTheoretical Computer Science (TCS), 2011
V. Pestov
202
2
0
27 May 2011
Bounding the Fat Shattering Dimension of a Composition Function Class
  Built Using a Continuous Logic Connective
Bounding the Fat Shattering Dimension of a Composition Function Class Built Using a Continuous Logic Connective
H. Duan
CoGe
113
10
0
23 May 2011
1
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