[ACM Press the twenty-seventh annual ACM symposium - Las Vegas, Nevada, United States (1995.05.29-1995.06.01)] Proceedings of the twenty-seventh annual ACM symposium on Theory of computing - STOC '95 - Polynomial bounds for VC dimension of sigmoidal neural networks

✍ Scribed by Karpinski, Marek; Macintyre, Angus

• Book ID: 111675904
• Publisher: ACM Press
• Year: 1995
• Tongue: English
• Weight: 647 KB
• Volume: 0
• Category: Article
• ISBN-13: 9780897917186
• DOI: 10.1145/225058.225118

✦ Synopsis

We introduce a new method for proving explicit upper bounds on the VC Dimension of general functional basis networks, and prove as an application, for the first time, the VC Dimension of analog neural networks with the sigmoid activation function o(y) = 1/1 + e-y to be bounded by a quadratic polynomial in the number of programmable parameters.