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» Learning Models for Multi-Source Integration
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ICDAR
2009
IEEE
15 years 6 months ago
Learning Rich Hidden Markov Models in Document Analysis: Table Location
Hidden Markov Models (HMM) are probabilistic graphical models for interdependent classification. In this paper we experiment with different ways of combining the components of an ...
Ana Costa e Silva
99
Voted
NAACL
2010
14 years 9 months ago
Learning Dense Models of Query Similarity from User Click Logs
The goal of this work is to integrate query similarity metrics as features into a dense model that can be trained on large amounts of query log data, in order to rank query rewrit...
Fabio De Bona, Stefan Riezler, Keith Hall, Massimi...
MTA
2002
103views more  MTA 2002»
14 years 11 months ago
STEPS: Supporting Traditional Education Procedures-A TCP/IP Multimedia Networks-Based Model
This paper describes an integrated model for the realization of an Open and Distance Learning (ODL) environment supporting traditional learning procedures, through collaborative le...
Christos Bouras, Petros Lampsas, Paul G. Spirakis
ICCV
2001
IEEE
16 years 1 months ago
Learning the Semantics of Words and Pictures
We present a statistical model for organizing image collections which integrates semantic information provided by associated text and visual information provided by image features...
Kobus Barnard, David A. Forsyth
ICML
2005
IEEE
16 years 16 days ago
Learning as search optimization: approximate large margin methods for structured prediction
Mappings to structured output spaces (strings, trees, partitions, etc.) are typically learned using extensions of classification algorithms to simple graphical structures (eg., li...
Daniel Marcu, Hal Daumé III