Efficient Agnostic Learning of Neural Networks with Bounded Fan-in (1996)

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by Wee Sun Lee , Peter L. Bartlett , Robert C. Williamson
Citations:68 - 18 self

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5 Agnostic Learning and Single Hidden Layer Neural Networks – Wee Sun Lee - 1996
13 The Informational Complexity of Learning from Examples – Partha Niyogi - 1996
14 On Efficient Agnostic Learning of Linear Combinations of Basis Functions – Wee Sun Lee, Peter L. Bartlett, Robert C. Williamson - 1995
47 On the Relationship Between Generalization Error, Hypothesis Complexity, and Sample Complexity for Radial Basis Functions – Partha Niyogi, Federico Girosi - 1996
!()+, -./01 23456 – Department Of Computer, David P. Dobkin, Dimitrios Gunopulos, Wolfgang Maass, Technische Universitaet Graz - 1995
12 Learning by Canonical Smooth Estimation, Part I: Simultaneous Estimation – Kevin L. Buescher, P. R. Kumar - 1996
177 The Sample Complexity of Pattern Classification With Neural Networks: The Size of the Weights is More Important Than the Size of the Network – Peter L. Bartlett - 1997
18 Probabilistic Analysis of Learning in Artificial Neural Networks: The PAC Model and its Variants – Martin Anthony - 1997
9 Learnability of Bipartite Ranking Functions – Shivani Agarwal, Dan Roth - 2005
13 Learning by Canonical Smooth Estimation, Part II: Learning and Choice of Model Complexity – Kevin L. Buescher, P. R. Kumar
Computational Learning Theory – Sally A. Goldman
721 Boosting the margin: A new explanation for the effectiveness of voting methods – Robert E. Schapire, Peter Bartlett, Yoav Freund, Wee Sun Lee - 1997
31 Generalization Bounds for Function Approximation from Scattered Noisy Data – Partha Niyogi, Federico Girosi - 1998
309 Regularization Theory and Neural Networks Architectures – Federico Girosi, Michael Jones, Tomaso Poggio - 1995
6 Mathematical Aspects of Neural Networks – B. Hammer, T. Villmann - 2003
4 Part 1: Overview of the Probably Approximately Correct (PAC) Learning Framework – David Haussler - 1995
9 Cross-Validation for Binary Classification by Real-Valued Functions: Theoretical Analysis – Martin Anthony, Sean B. Holden - 1999
3 Knowledge acquisition in statistical learning theory – Shai Fine - 1999
61 Fat-shattering and the learnability of real-valued functions – Peter L. Bartlett, Philip M. Long, Robert C. Williamson - 1996