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138
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GECCO
2009
Springer
204views Optimization» more  GECCO 2009»
15 years 7 months ago
Combined structure and motion extraction from visual data using evolutionary active learning
We present a novel stereo vision modeling framework that generates approximate, yet physically-plausible representations of objects rather than creating accurate models that are c...
Krishnanand N. Kaipa, Josh C. Bongard, Andrew N. M...
114
Voted
WWW
2004
ACM
16 years 3 months ago
Ontological representation of learning objects: building interoperable vocabulary and structures
The ontological representation of learning objects is a way to deal with the interoperability and reusability of learning objects (including metadata) through providing a semantic...
Jian Qin, Naybell Hernández
IJCAI
2007
15 years 4 months ago
Change of Representation for Statistical Relational Learning
Statistical relational learning (SRL) algorithms learn statistical models from relational data, such as that stored in a relational database. We previously introduced view learnin...
Jesse Davis, Irene M. Ong, Jan Struyf, Elizabeth S...
ECCV
2002
Springer
16 years 4 months ago
Multimodal Data Representations with Parameterized Local Structures
Abstract. In many vision problems, the observed data lies in a nonlinear manifold in a high-dimensional space. This paper presents a generic modelling scheme to characterize the no...
Ying Zhu, Dorin Comaniciu, Stuart C. Schwartz, Vis...
132
Voted
NN
2008
Springer
201views Neural Networks» more  NN 2008»
15 years 2 months ago
Learning representations for object classification using multi-stage optimal component analysis
Learning data representations is a fundamental challenge in modeling neural processes and plays an important role in applications such as object recognition. In multi-stage Optima...
Yiming Wu, Xiuwen Liu, Washington Mio