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IJCAI
2007
13 years 9 months ago
Simple Training of Dependency Parsers via Structured Boosting
Recently, significant progress has been made on learning structured predictors via coordinated training algorithms such as conditional random fields and maximum margin Markov ne...
Qin Iris Wang, Dekang Lin, Dale Schuurmans
ACML
2009
Springer
14 years 3 months ago
Injecting Structured Data to Generative Topic Model in Enterprise Settings
Enterprises have accumulated both structured and unstructured data steadily as computing resources improve. However, previous research on enterprise data mining often treats these ...
Han Xiao, Xiaojie Wang, Chao Du
CIBCB
2008
IEEE
14 years 2 months ago
Temporal and structural analysis of biological networks in combination with microarray data
— We introduce a graph-based relational learning approach using graph-rewriting rules for temporal and structural analysis of biological networks changing over time. The analysis...
Chang Hun You, Lawrence B. Holder, Diane J. Cook
ICML
2009
IEEE
14 years 9 months ago
Learning nonlinear dynamic models
We present a novel approach for learning nonlinear dynamic models, which leads to a new set of tools capable of solving problems that are otherwise difficult. We provide theory sh...
John Langford, Ruslan Salakhutdinov, Tong Zhang
GECCO
2006
Springer
177views Optimization» more  GECCO 2006»
14 years 9 hour ago
Hyper-ellipsoidal conditions in XCS: rotation, linear approximation, and solution structure
The learning classifier system XCS is an iterative rulelearning system that evolves rule structures based on gradient-based prediction and rule quality estimates. Besides classifi...
Martin V. Butz, Pier Luca Lanzi, Stewart W. Wilson