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» Learning Probabilistic Models of Link Structure
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109
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AAAI
2011
13 years 9 months ago
Coarse-to-Fine Inference and Learning for First-Order Probabilistic Models
Coarse-to-fine approaches use sequences of increasingly fine approximations to control the complexity of inference and learning. These techniques are often used in NLP and visio...
Chloe Kiddon, Pedro Domingos
ICDM
2003
IEEE
100views Data Mining» more  ICDM 2003»
15 years 2 months ago
Tractable Group Detection on Large Link Data Sets
Discovering underlying structure from co-occurrence data is an important task in a variety of fields, including: insurance, intelligence, criminal investigation, epidemiology, hu...
Jeremy Kubica, Andrew W. Moore, Jeff G. Schneider
ACCV
2006
Springer
15 years 3 months ago
Probabilistic Modeling for Structural Change Inference
We view the task of change detection as a problem of object recognition from learning. The object is defined in a 3D space where the time is the 3rd dimension. We propose two com...
Wei Liu, Véronique Prinet
97
Voted
TFS
2008
129views more  TFS 2008»
14 years 8 months ago
A Functional-Link-Based Neurofuzzy Network for Nonlinear System Control
Abstract--This study presents a functional-link-based neurofuzzy network (FLNFN) structure for nonlinear system control. The proposed FLNFN model uses a functional link neural netw...
Cheng-Hung Chen, Cheng-Jian Lin, Chin-Teng Lin
ACL
2003
14 years 11 months ago
Probabilistic Text Structuring: Experiments with Sentence Ordering
Ordering information is a critical task for natural language generation applications. In this paper we propose an approach to information ordering that is particularly suited for ...
Mirella Lapata