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» An Introduction to Learning Structured Information
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JMLR
2012
11 years 7 months ago
Structured Output Learning with High Order Loss Functions
Often when modeling structured domains, it is desirable to leverage information that is not naturally expressed as simply a label. Examples include knowledge about the evaluation ...
Daniel Tarlow, Richard S. Zemel
LEGE
2004
103views Education» more  LEGE 2004»
13 years 6 months ago
Structuring and merging Distributed Content
A flexible approach for structuring and merging distributed learning object is presented. At the basis of this approach there is a formal representation of a learning object, call...
Luca Stefanutti, Dietrich Albert, Cord Hockemeyer
KDD
2009
ACM
230views Data Mining» more  KDD 2009»
13 years 10 months ago
Grouped graphical Granger modeling methods for temporal causal modeling
We develop and evaluate an approach to causal modeling based on time series data, collectively referred to as“grouped graphical Granger modeling methods.” Graphical Granger mo...
Aurelie C. Lozano, Naoki Abe, Yan Liu, Saharon Ros...
BIS
2007
120views Business» more  BIS 2007»
13 years 6 months ago
Security Issues for the Use of Semantic Web in E-Commerce
As the ontologies are the pivotal element of the Semantic Web in E-Commerce, it is necessary to protect the ontology’s integrity and availability. In addition, both suppliers and...
Andreas Ekelhart, Stefan Fenz, A. Min Tjoa, Edgar ...
CIKM
2011
Springer
12 years 5 months ago
Semi-supervised multi-task learning of structured prediction models for web information extraction
Extracting information from web pages is an important problem; it has several applications such as providing improved search results and construction of databases to serve user qu...
Paramveer S. Dhillon, Sundararajan Sellamanickam, ...