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ICML
2007
IEEE
16 years 4 months ago
Spectral feature selection for supervised and unsupervised learning
Feature selection aims to reduce dimensionality for building comprehensible learning models with good generalization performance. Feature selection algorithms are largely studied ...
Zheng Zhao, Huan Liu
CORR
2008
Springer
108views Education» more  CORR 2008»
15 years 3 months ago
Resolution Trees with Lemmas: Resolution Refinements that Characterize DLL Algorithms with Clause Learning
Resolution refinements called w-resolution trees with lemmas (WRTL) and with input lemmas (WRTI) are introduced. Dag-like resolution is equivalent to both WRTL and WRTI when there...
Samuel R. Buss, Jan Hoffmann 0002, Jan Johannsen
145
Voted
PR
2010
156views more  PR 2010»
15 years 2 months ago
Semi-supervised clustering with metric learning: An adaptive kernel method
Most existing representative works in semi-supervised clustering do not sufficiently solve the violation problem of pairwise constraints. On the other hand, traditional kernel met...
Xuesong Yin, Songcan Chen, Enliang Hu, Daoqiang Zh...
152
Voted
AAAI
2012
13 years 6 months ago
Transfer Learning with Graph Co-Regularization
Transfer learning proves to be effective for leveraging labeled data in the source domain to build an accurate classifier in the target domain. The basic assumption behind transf...
Mingsheng Long, Jianmin Wang 0001, Guiguang Ding, ...
ECML
2000
Springer
15 years 8 months ago
Layered Learning
We examine how a network of many knowledge layers can be constructed in an on-line manner, such that the learned units represent building blocks of knowledge that serve to compres...
Peter Stone, Manuela M. Veloso