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» The complexity of properly learning simple concept classes
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ICML
2009
IEEE
14 years 5 months ago
Surrogate regret bounds for proper losses
We present tight surrogate regret bounds for the class of proper (i.e., Fisher consistent) losses. The bounds generalise the margin-based bounds due to Bartlett et al. (2006). The...
Mark D. Reid, Robert C. Williamson
ALT
1997
Springer
13 years 9 months ago
Learning DFA from Simple Examples
Efficient learning of DFA is a challenging research problem in grammatical inference. It is known that both exact and approximate (in the PAC sense) identifiability of DFA is har...
Rajesh Parekh, Vasant Honavar
ML
2002
ACM
220views Machine Learning» more  ML 2002»
13 years 4 months ago
Bayesian Methods for Support Vector Machines: Evidence and Predictive Class Probabilities
I describe a framework for interpreting Support Vector Machines (SVMs) as maximum a posteriori (MAP) solutions to inference problems with Gaussian Process priors. This probabilisti...
Peter Sollich
BMCBI
2006
150views more  BMCBI 2006»
13 years 4 months ago
Instance-based concept learning from multiclass DNA microarray data
Background: Various statistical and machine learning methods have been successfully applied to the classification of DNA microarray data. Simple instance-based classifiers such as...
Daniel P. Berrar, Ian Bradbury, Werner Dubitzky
CN
2010
95views more  CN 2010»
13 years 4 months ago
Loop-free alternates and not-via addresses: A proper combination for IP fast reroute?
The IETF currently discusses fast reroute mechanisms for IP networks (IP FRR). IP FRR accelerates the recovery in case of network element failures and avoids micro-loops during re...
Michael Menth, Matthias Hartmann, Rüdiger Mar...