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» A Model Selection Approach for Local Learning
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ICML
2002
IEEE
14 years 8 months ago
Is Combining Classifiers Better than Selecting the Best One
We empirically evaluate several state-of-theart methods for constructing ensembles of heterogeneous classifiers with stacking and show that they perform (at best) comparably to se...
Saso Dzeroski, Bernard Zenko
KDD
2008
ACM
183views Data Mining» more  KDD 2008»
14 years 8 months ago
Knowledge transfer via multiple model local structure mapping
The effectiveness of knowledge transfer using classification algorithms depends on the difference between the distribution that generates the training examples and the one from wh...
Jing Gao, Wei Fan, Jing Jiang, Jiawei Han
CRYPTO
2003
Springer
187views Cryptology» more  CRYPTO 2003»
14 years 23 days ago
On Constructing Locally Computable Extractors and Cryptosystems in the Bounded Storage Model
We consider the problem of constructing randomness extractors that are locally computable; that is, read only a small number of bits from their input. As recently shown by Lu (thi...
Salil P. Vadhan
ACL
2009
13 years 5 months ago
Automatically Generating Wikipedia Articles: A Structure-Aware Approach
In this paper, we investigate an approach for creating a comprehensive textual overview of a subject composed of information drawn from the Internet. We use the high-level structu...
Christina Sauper, Regina Barzilay
ICCV
2011
IEEE
12 years 7 months ago
Actively Selecting Annotations Among Objects and Attributes
We present an active learning approach to choose image annotation requests among both object category labels and the objects’ attribute labels. The goal is to solicit those labe...
Adriana Kovashka, Sudheendra Vijayanarasimhan, Kri...