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NIPS
2008
13 years 10 months ago
Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data
Inspired by the hierarchical hidden Markov models (HHMM), we present the hierarchical semi-Markov conditional random field (HSCRF), a generalisation of embedded undirected Markov ...
Tran The Truyen, Dinh Q. Phung, Hung Hai Bui, Svet...
ECAI
2008
Springer
13 years 10 months ago
Multilingual Evidence Improves Clustering-based Taxonomy Extraction
We present a system for taxonomy extraction, aimed at providing a taxonomic backbone in an ontology learning environment. We follow previous research in using hierarchical clusteri...
Hans Hjelm, Paul Buitelaar
JMLR
2010
144views more  JMLR 2010»
13 years 3 months ago
Maximum Margin Learning with Incomplete Data: Learning Networks instead of Tables
In this paper we address the problem of predicting when the available data is incomplete. We show that changing the generally accepted table-wise view of the sample items into a g...
Sándor Szedmák, Yizhao Ni, Steve R. ...
WOA
2001
13 years 10 months ago
Implementing Adaptive Capabilities on Agents that Act in a Dynamic Environment
Acting in a dynamic environment is a complex task that requires several issues to be investigated, with the aim of controlling the associated search complexity. In this paper, a l...
Giuliano Armano, Giancarlo Cherchi, Eloisa Vargiu
ICIP
2008
IEEE
14 years 10 months ago
A supervised nonlinear neighborhood embedding of color histogram for image indexing
Subspace learning techniques are widespread in pattern recognition research. They include PCA, ICA, LPP, etc. These techniques are generally linear and unsupervised. The problem o...
Xian-Hua Han, Yen-Wei Chen, Takeshi Sukegawa