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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»
16 years 2 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
15 years 8 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»
13 years 4 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
15 years 8 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
16 years 3 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