Sciweavers

463 search results - page 37 / 93
» Induction in Noisy Domains
Sort
View
AAAI
2011
13 years 11 months ago
Using Semantic Cues to Learn Syntax
We present a method for dependency grammar induction that utilizes sparse annotations of semantic relations. This induction set-up is attractive because such annotations provide u...
Tahira Naseem, Regina Barzilay
JMLR
2010
104views more  JMLR 2010»
14 years 6 months ago
Increasing Feature Selection Accuracy for L1 Regularized Linear Models
L1 (also referred to as the 1-norm or Lasso) penalty based formulations have been shown to be effective in problem domains when noisy features are present. However, the L1 penalty...
Abhishek Jaiantilal, Gregory Z. Grudic
ILP
2004
Springer
15 years 5 months ago
Learning Ensembles of First-Order Clauses for Recall-Precision Curves: A Case Study in Biomedical Information Extraction
Many domains in the field of Inductive Logic Programming (ILP) involve highly unbalanced data. Our research has focused on Information Extraction (IE), a task that typically invol...
Mark Goadrich, Louis Oliphant, Jude W. Shavlik
AND
2009
14 years 9 months ago
Kernel-based relation extraction from investigative data
In a specific process of business intelligence, i.e. investigation on organized crime, empirical language processing technologies can play a crucial role. In the data used on inve...
Cristina Giannone, Roberto Basili, Chiara Del Vesc...
ATAL
2008
Springer
15 years 1 months ago
Selecting strategies using empirical game models: an experimental analysis of meta-strategies
In many complex multi-agent domains it is impractical to compute exact analytic solutions. An alternate means of analysis applies computational tools to derive and analyze empiric...
Christopher Kiekintveld, Michael P. Wellman