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Boolean Functions and Artificial Neural Networks
– Martin Anthony Department, Martin Anthony
- 2003
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7
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Margin-based generalization error bounds for threshold decision lists
– Martin Anthony
- 2003
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Connections between Neural Networks and Boolean Functions ∗
– Martin Anthony
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16
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Probabilistic Analysis of Learning in Artificial Neural Networks: The PAC Model and its Variants
– Martin Anthony
- 1994
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3
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Quantifying generalization in linearly weighted neural networks
– Martin Anthony, Sean B. Holden
- 1994
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3
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Part 1: Overview of the Probably Approximately Correct (PAC) Learning Framework
– David Haussler
- 1995
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Threshold networks for pattern classification
– Martin Anthony
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5
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Sequential Constructive Techniques
– Marco Muselli
- 1998
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156
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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
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7
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Threshold Functions, Decision Lists, and the Representation of Boolean Functions
– Martin Anthony
- 1996
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Mathematical Modelling of Generalization
– Martin Anthony
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1
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Uniform Glivenko-Cantelli Theorems and Concentration of Measure in the . . .
– Martin Anthony
- 2002
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!()+, -./01 23456
– Department Of Computer, David P. Dobkin, Dimitrios Gunopulos, Wolfgang Maass, Technische Universitaet Graz
- 1995
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30
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Introduction to Statistical Learning Theory
– Olivier Bousquet, Stéphane Boucheron, Gábor Lugosi
- 2004
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1
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Partitioning points by parallel planes
– Martin Anthony
- 2002
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18
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FROM FINDING MAXIMUM FEASIBLE SUBSYSTEMS OF LINEAR SYSTEMS TO FEEDFORWARD NEURAL NETWORK DESIGN
– Edoardo Amaldi
- 1994
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14
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A Framework for Structural Risk Minimisation
– John Shawe-taylor, Royal Holloway, Peter L. Bartlett, Systems Engineering Dept, Robert C. Williamson, Engineering Dept, Martin Anthony
- 1996
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12
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Sequential PAC Learning
– Dale Schuurmans, Russell Greiner
- 1995
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1
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Accuracy of techniques for the logical analysis of data, Rutcor Research Raport
– Martin Anthony
- 1996
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