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» An Introduction to Learning Structured Information
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MM
2005
ACM
209views Multimedia» more  MM 2005»
15 years 9 months ago
Learning an image-word embedding for image auto-annotation on the nonlinear latent space
Latent Semantic Analysis (LSA) has shown encouraging performance for the problem of unsupervised image automatic annotation. LSA conducts annotation by keywords propagation on a l...
Wei Liu, Xiaoou Tang
130
Voted
ECTEL
2006
Springer
15 years 7 months ago
A Formal Model of Learning Object Metadata
In this paper, we introduce a new, formal model of learning object metadata. The model enables more formal, rigorous reasoning over metadata. An important feature of the model is t...
Kris Cardinaels, Erik Duval, Henk J. Olivié
109
Voted
ICML
2009
IEEE
16 years 4 months ago
K-means in space: a radiation sensitivity evaluation
Spacecraft increasingly employ onboard data analysis to inform further data collection and prioritization decisions. However, many spacecraft operate in high-radiation environment...
Kiri L. Wagstaff, Benjamin Bornstein
WIRN
2005
Springer
15 years 9 months ago
Recursive Neural Networks and Graphs: Dealing with Cycles
Recursive neural networks are a powerful tool for processing structured data. According to the recursive learning paradigm, the input information consists of directed positional ac...
Monica Bianchini, Marco Gori, Lorenzo Sarti, Franc...
NIPS
2007
15 years 5 months ago
Modeling Natural Sounds with Modulation Cascade Processes
Natural sounds are structured on many time-scales. A typical segment of speech, for example, contains features that span four orders of magnitude: Sentences (∼1 s); phonemes (âˆ...
Richard Turner, Maneesh Sahani