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EMNLP
2006
14 years 11 months ago
Competitive generative models with structure learning for NLP classification tasks
In this paper we show that generative models are competitive with and sometimes superior to discriminative models, when both kinds of models are allowed to learn structures that a...
Kristina Toutanova
BMVC
2010
14 years 8 months ago
Multi-class Boosting for Early Classification of Sequences
We propose a new boosting algorithm for sequence classification, in particular one that enables early classification of multiple classes. In many practical problems, we would like...
Katsuhiko Ishiguro, Hiroshi Sawada, Hitoshi Sakano
WWW
2009
ACM
15 years 10 months ago
Graffiti: node labeling in heterogeneous networks
We introduce a multi-label classification model and algorithm for labeling heterogeneous networks, where nodes belong to different types and different types have different sets of...
Ralitsa Angelova, Gjergji Kasneci, Fabian M. Sucha...
NPL
2006
90views more  NPL 2006»
14 years 9 months ago
Hierarchical Incremental Class Learning with Reduced Pattern Training
Hierarchical Incremental Class Learning (HICL) is a new task decomposition method that addresses the pattern classification problem. HICL is proven to be a good classifier but clos...
Sheng Uei Guan, Chunyu Bao, Ru-Tian Sun
OAS
2003
14 years 11 months ago
A UML ontology and derived content language for a travel booking scenario
This paper illustrates an approach to combining the benefits of a multi-agent system architecture with the use of industry-standard modelling techniques using the Unified Modeli...
Stephen Cranefield, Jin Pan, Martin K. Purvis