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» Learning the parts of objects by auto-association
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KDD
2008
ACM
119views Data Mining» more  KDD 2008»
14 years 8 months ago
SAIL: summation-based incremental learning for information-theoretic clustering
Information-theoretic clustering aims to exploit information theoretic measures as the clustering criteria. A common practice on this topic is so-called INFO-K-means, which perfor...
Junjie Wu, Hui Xiong, Jian Chen
IJCNN
2007
IEEE
14 years 1 months ago
Robotic Architecture Inspired on Behavior Analysis
Learning by human tutelage means that a human being guides the attention of a robot or agent in order to teach it a given concept. This kind of learning is very important to devel...
Claudio A. Policastro, Roseli A. F. Romero, Giovan...
KDD
2012
ACM
190views Data Mining» more  KDD 2012»
11 years 10 months ago
Multi-label hypothesis reuse
Multi-label learning arises in many real-world tasks where an object is naturally associated with multiple concepts. It is well-accepted that, in order to achieve a good performan...
Sheng-Jun Huang, Yang Yu, Zhi-Hua Zhou
AIED
2009
Springer
14 years 2 months ago
What Students Expect May Have More Impact Than What They Know or Feel
Researchers of educational technologies are often asked to do the impossible: make students learn and have them enjoy it. These two objectives, though not mutually exclusive, are f...
G. Tanner Jackson, Arthur C. Graesser, Danielle S....
ICIP
2006
IEEE
14 years 9 months ago
A Probabilistic Approach to Robust Shape Matching
We present a probabilistic approach to shape matching which is invariant to rotation, translation and scaling. Shapes are represented by unlabeled point sets, so discontinuous bou...
Graham McNeill, Sethu Vijayakumar