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ACL
2011
12 years 11 months ago
The Surprising Variance in Shortest-Derivation Parsing
We investigate full-scale shortest-derivation parsing (SDP), wherein the parser selects an analysis built from the fewest number of training fragments. Shortest derivation parsing...
Mohit Bansal, Dan Klein
FUZZIEEE
2007
IEEE
14 years 1 months ago
Learning Fuzzy Linguistic Models from Low Quality Data by Genetic Algorithms
— Incremental rule base learning techniques can be used to learn models and classifiers from interval or fuzzyvalued data. These algorithms are efficient when the observation e...
Luciano Sánchez, José Otero
JMLR
2011
110views more  JMLR 2011»
13 years 2 months ago
Training SVMs Without Offset
We develop, analyze, and test a training algorithm for support vector machine classifiers without offset. Key features of this algorithm are a new, statistically motivated stoppi...
Ingo Steinwart, Don R. Hush, Clint Scovel
ISIPTA
2005
IEEE
161views Mathematics» more  ISIPTA 2005»
14 years 1 months ago
Decision making under incomplete data using the imprecise Dirichlet model
The paper presents an efficient solution to decision problems where direct partial information on the distribution of the states of nature is available, either by observations of ...
Lev V. Utkin, Thomas Augustin
PG
2003
IEEE
14 years 22 days ago
Hierarchical Least Squares Conformal Map
A texture atlas is an efficient way to represent information (like colors, normals, displacement maps ...) on triangulated surfaces. The LSCM method (Least Squares Conformal Maps...
Nicolas Ray, Bruno Lévy