1106 search results - page 67 / 222 » On regularization algorithms in learning theory |
133
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PKDD
2010
Springer
15 years 2 months ago
2010
Springer
We consider the problem of numerical stability and model density growth when training a sparse linear model from massive data. We focus on scalable algorithms that optimize certain...
130
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ACMICEC
2007
ACM
15 years 9 months ago
2007
ACM
This paper introduces algorithms for learning how to trade using insider (superior) information in Kyle's model of financial markets. Prior results in finance theory relied o...
199
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ICALP
2011
Springer
14 years 8 months ago
2011
Springer
We give new algorithms for a variety of randomly-generated instances of computational problems using a linearization technique that reduces to solving a system of linear equations...
150
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SSPR
1998
Springer
15 years 9 months ago
1998
Springer
A novel method to improve the generalization performance of the Minimum Classification Error (MCE) / Generalized Probabilistic Descent (GPD) learning is proposed. The MCE/GPD learn...
222
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Lab
Our research is motivated by a strong conviction that business processes in electronic enterprises can be designed to deliver high levels of performance through the use of mathemat...