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» Is an ordinal class structure useful in classifier learning
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ICPR
2002
IEEE
14 years 8 months ago
To Each According to its Need: Kernel Class Specific Classifiers
We present in this paper a new multi-class Bayes classifier that permits using separate feature vectors, chosen specifically for each class. This technique extends previous work o...
Barbara Caputo, Heinrich Niemann
ISNN
2004
Springer
14 years 25 days ago
Unsupervised Learning for Hierarchical Clustering Using Statistical Information
This paper proposes a novel hierarchical clustering method that can classify given data without specified knowledge of the number of classes. In this method, at each node of a hie...
Masaru Okamoto, Nan Bu, Toshio Tsuji
MICCAI
2000
Springer
13 years 11 months ago
Small Sample Size Learning for Shape Analysis of Anatomical Structures
We present a novel approach to statistical shape analysis of anatomical structures based on small sample size learning techniques. The high complexity of shape models used in medic...
Polina Golland, W. Eric L. Grimson, Martha Elizabe...
COLT
1999
Springer
13 years 11 months ago
On a Generalized Notion of Mistake Bounds
This paper proposes the use of constructive ordinals as mistake bounds in the on-line learning model. This approach elegantly generalizes the applicability of the on-line mistake ...
Sanjay Jain, Arun Sharma
IDEAL
2004
Springer
14 years 25 days ago
Learning to Classify Biomedical Terms Through Literature Mining and Genetic Algorithms.
We present an approach to classification of biomedical terms based on the information acquired automatically from the corpus of relevant literature. The learning phase consists of...
Irena Spasic, Goran Nenadic, Sophia Ananiadou