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COLT
1994
Springer
15 years 8 months ago
Bayesian Inductive Logic Programming
Inductive Logic Programming (ILP) involves the construction of first-order definite clause theories from examples and background knowledge. Unlike both traditional Machine Learnin...
Stephen Muggleton
PPSN
2004
Springer
15 years 9 months ago
The Application of Bayesian Optimization and Classifier Systems in Nurse Scheduling
Two ideas taken from Bayesian optimization and classifier systems are presented for personnel scheduling based on choosing a suitable scheduling rule from a set for each person’s...
Jingpeng Li, Uwe Aickelin
AI
2005
Springer
15 years 10 months ago
A Supervised Learning Approach to Acronym Identification
This paper addresses the task of finding acronym-definition pairs in text. Most of the previous work on the topic is about systems that involve manually generated rules or regular ...
David Nadeau, Peter D. Turney
COLT
2005
Springer
15 years 10 months ago
Analysis of Perceptron-Based Active Learning
We start by showing that in an active learning setting, the Perceptron algorithm needs Ω( 1 ε2 ) labels to learn linear separators within generalization error ε. We then prese...
Sanjoy Dasgupta, Adam Tauman Kalai, Claire Montele...
IDA
2005
Springer
15 years 10 months ago
Learning from Ambiguously Labeled Examples
Inducing a classification function from a set of examples in the form of labeled instances is a standard problem in supervised machine learning. In this paper, we are concerned w...
Eyke Hüllermeier, Jürgen Beringer