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» A General Feature Space for Automatic Verb Classification
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ICCV
2003
IEEE
16 years 5 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
144
Voted
JMLR
2010
206views more  JMLR 2010»
14 years 10 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...
134
Voted
ICPR
2010
IEEE
15 years 1 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 4 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...
268
Voted
PLDI
2009
ACM
16 years 4 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...