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» A General Feature Space for Automatic Verb Classification
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ICCV
2003
IEEE
16 years 8 months ago
Minimally-Supervised Classification using Multiple Observation Sets
This paper discusses building complex classifiers from a single labeled example and vast number of unlabeled observation sets, each derived from observation of a single process or...
Chris Stauffer
JMLR
2010
206views more  JMLR 2010»
15 years 1 months ago
Learning Translation Invariant Kernels for Classification
Appropriate selection of the kernel function, which implicitly defines the feature space of an algorithm, has a crucial role in the success of kernel methods. In this paper, we co...
Sayed Kamaledin Ghiasi Shirazi, Reza Safabakhsh, M...
ICPR
2010
IEEE
15 years 4 months ago
Boosting Bayesian MAP Classification
In this paper we redefine and generalize the classic k-nearest neighbors (k-NN) voting rule in a Bayesian maximum-a-posteriori (MAP) framework. Therefore, annotated examples are u...
Paolo Piro, Richard Nock, Frank Nielsen, Michel Ba...
KDD
2009
ACM
156views Data Mining» more  KDD 2009»
16 years 7 months ago
Effective multi-label active learning for text classification
Labeling text data is quite time-consuming but essential for automatic text classification. Especially, manually creating multiple labels for each document may become impractical ...
Bishan Yang, Jian-Tao Sun, Tengjiao Wang, Zheng Ch...
PLDI
2009
ACM
16 years 7 months ago
Automatic generation of library bindings using static analysis
High-level languages are growing in popularity. However, decades of C software development have produced large libraries of fast, timetested, meritorious code that are impractical...
Tristan Ravitch, Steve Jackson, Eric Aderhold, Ben...