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TSP
2008
151views more  TSP 2008»
13 years 9 months ago
Reduce and Boost: Recovering Arbitrary Sets of Jointly Sparse Vectors
The rapid developing area of compressed sensing suggests that a sparse vector lying in a high dimensional space can be accurately and efficiently recovered from only a small set of...
Moshe Mishali, Yonina C. Eldar
ICANN
2007
Springer
14 years 4 months ago
Sparse Least Squares Support Vector Regressors Trained in the Reduced Empirical Feature Space
Abstract. In this paper we discuss sparse least squares support vector regressors (sparse LS SVRs) defined in the reduced empirical feature space, which is a subspace of mapped tr...
Shigeo Abe, Kenta Onishi
ICDM
2006
IEEE
118views Data Mining» more  ICDM 2006»
14 years 4 months ago
Generalizing Version Space Support Vector Machines for Non-Separable Data
Although version space support vector machines (VSSVMs) are a successful approach to reliable classification [6], they are restricted to separable data. This paper proposes gener...
Evgueni N. Smirnov, Ida G. Sprinkhuizen-Kuyper, Ni...
NAACL
2010
13 years 7 months ago
Cross-lingual Induction of Selectional Preferences with Bilingual Vector Spaces
We describe a cross-lingual method for the induction of selectional preferences for resourcepoor languages, where no accurate monolingual models are available. The method uses bil...
Yves Peirsman, Sebastian Padó
COLING
2002
13 years 9 months ago
Word Sense Disambiguation using Static and Dynamic Sense Vectors
It is popular in WSD to use contextual information in training sense tagged data. Co-occurring words within a limited window-sized context support one sense among the semantically...
Jong-Hoon Oh, Key-Sun Choi