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» Learning the Semantics of Words and Pictures
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ACL
2012
11 years 10 months ago
Improving Word Representations via Global Context and Multiple Word Prototypes
Unsupervised word representations are very useful in NLP tasks both as inputs to learning algorithms and as extra word features in NLP systems. However, most of these models are b...
Eric H. Huang, Richard Socher, Christopher D. Mann...
CSL
2002
Springer
13 years 7 months ago
Learning visually grounded words and syntax for a scene description task
A spoken language generation system has been developed that learns to describe objects in computer-generated visual scenes. The system is trained by a `show-and-tell' procedu...
Deb K. Roy
ICTIR
2009
Springer
14 years 2 months ago
Robust Word Similarity Estimation Using Perturbation Kernels
We introduce perturbation kernels, a new class of similarity measure for information retrieval that casts word similarity in terms of multi-task learning. Perturbation kernels mode...
Kevyn Collins-Thompson
FLAIRS
2004
13 years 9 months ago
Combining Methods for Word Sense Disambiguation of WordNet Glosses
This paper presents a new approach for combining different semantic disambiguation methods that are part of a Word Sense Disambiguation(WSD) system. The way these methods are comb...
Adrian Novischi
IR
2010
13 years 6 months ago
Learning to rank with (a lot of) word features
In this article we present Supervised Semantic Indexing (SSI) which defines a class of nonlinear (quadratic) models that are discriminatively trained to directly map from the word...
Bing Bai, Jason Weston, David Grangier, Ronan Coll...