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» Learning and Generalization with the Information Bottleneck
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KCAP
2009
ACM
15 years 4 months ago
Reducing class imbalance during active learning for named entity annotation
In lots of natural language processing tasks, the classes to be dealt with often occur heavily imbalanced in the underlying data set and classifiers trained on such skewed data t...
Katrin Tomanek, Udo Hahn
IUI
2011
ACM
14 years 27 days ago
TellMe: learning procedures from tutorial instruction
This paper describes an approach to allow end users to define new procedures through tutorial instruction. Our approach allows users to specify procedures in natural language in t...
Yolanda Gil, Varun Ratnakar, Christian Fritz
ICML
2005
IEEE
15 years 10 months ago
Predictive low-rank decomposition for kernel methods
Low-rank matrix decompositions are essential tools in the application of kernel methods to large-scale learning problems. These decompositions have generally been treated as black...
Francis R. Bach, Michael I. Jordan
ICML
2003
IEEE
15 years 10 months ago
An Analysis of Rule Evaluation Metrics
In this paper we analyze the most popular evaluation metrics for separate-and-conquer rule learning algorithms. Our results show that all commonly used heuristics, including accur...
Johannes Fürnkranz, Peter A. Flach
ITICSE
2004
ACM
15 years 3 months ago
The backwash effect on SQL skills grading
This paper examines the effect of grading approaches for SQL query formulation on students’ learning strategies. The way that students are graded in a subject has a significant ...
Julia Coleman Prior, Raymond Lister