95 search results - page 10 / 19 » Learning Textual Entailment on a Distance Feature Space |
IJCAI
2007
13 years 8 months ago
2007
Dimensionality reduction is a much-studied task in machine learning in which high-dimensional data is mapped, possibly via a non-linear transformation, onto a low-dimensional mani...
ESWS
2008
Springer
13 years 9 months ago
2008
Springer
Context-awareness is a highly desired feature across several application domains. Semantic Web Services (SWS) technologies address context-adaptation by enabling the automatic disc...
MM
2010
ACM
13 years 7 months ago
2010
ACM
This paper presents a supervised manifold learning model for dimensionality reduction in image and video classification tasks. Unlike most manifold learning models that emphasize ...
MM
2004
ACM
14 years 23 days ago
2004
ACM
We consider the problem of learning a mapping function from low-level feature space to high-level semantic space. Under the assumption that the data lie on a submanifold embedded ...
JCP
2008
13 years 7 months ago
2008
The Self Organizing Map (SOM) involves neural networks, that learns the features of input data thorough unsupervised, competitive neighborhood learning. In the SOM learning algorit...