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NIPS
2003
15 years 5 months ago
A Model for Learning the Semantics of Pictures
We propose an approach to learning the semantics of images which allows us to automatically annotate an image with keywords and to retrieve images based on text queries. We do thi...
Victor Lavrenko, R. Manmatha, Jiwoon Jeon
UAI
1998
15 years 5 months ago
Learning the Structure of Dynamic Probabilistic Networks
Dynamic probabilistic networks are a compact representation of complex stochastic processes. In this paper we examine how to learn the structure of a DPN from data. We extend stru...
Nir Friedman, Kevin P. Murphy, Stuart J. Russell
AAAI
1992
15 years 5 months ago
Learning to Disambiguate Relative Pronouns
In this paper we show how a natural language system can learn to find the antecedents of relative pronouns. We use a well-known conceptual clustering system to create a case-based...
Claire Cardie
ICANN
2010
Springer
15 years 5 months ago
A Learned Saliency Predictor for Dynamic Natural Scenes
Abstract. We investigate the extent to which eye movements in natural dynamic scenes can be predicted with a simple model of bottom-up saliency, which learns on different visual re...
Eleonora Vig, Michael Dorr, Thomas Martinetz, Erha...
NN
2006
Springer
15 years 4 months ago
Machine learning in sedimentation modelling
The paper presents machine learning (ML) models that predict sedimentation in the harbour basin of the Port of Rotterdam. The important factors affecting the sedimentation process...
Biswanath Bhattacharya, Dimitri P. Solomatine