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» Arguing from Experience to Classifying Noisy Data
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ECCV
2008
Springer
14 years 9 months ago
Automated Delineation of Dendritic Networks in Noisy Image Stacks
We present a novel approach to 3D delineation of dendritic networks in noisy image stacks. We achieve a level of automation beyond that of stateof-the-art systems, which model dend...
Germán González, François Fle...
LREC
2008
128views Education» more  LREC 2008»
13 years 9 months ago
Relation between Agreement Measures on Human Labeling and Machine Learning Performance: Results from an Art History Domain
We discuss factors that affect human agreement on a semantic labeling task in the art history domain, based on the results of four experiments where we varied the number of labels...
Rebecca J. Passonneau, Thomas Lippincott, Tae Yano...
ECML
1987
Springer
13 years 11 months ago
Induction in Noisy Domains
This paper examines the induction of classification rules from examples using real-world data. Real-world data is almost always characterized by two features, which are important ...
Peter Clark, Tim Niblett
COMMA
2008
13 years 9 months ago
Arguments from Experience: The PADUA Protocol
In this paper we describe PADUA, a protocol designed to enable agents to debate an issue drawing arguments not from a knowledge base of facts, rules and priorities but directly fro...
Maya Wardeh, Trevor J. M. Bench-Capon, Frans Coene...
KDD
2008
ACM
137views Data Mining» more  KDD 2008»
14 years 8 months ago
Learning classifiers from only positive and unlabeled data
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
Charles Elkan, Keith Noto