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» Learning to rank with multiple objective functions
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ICCV
2007
IEEE
16 years 1 months ago
Learning Auto-Structured Regressor from Uncertain Nonnegative Labels
In this paper, we take the human age and pose estimation problems as examples to study automatic designing regressor from training samples with uncertain nonnegative labels. First...
Shuicheng Yan, Huan Wang, Xiaoou Tang, Thomas S. H...
EUROCAST
2007
Springer
182views Hardware» more  EUROCAST 2007»
15 years 5 months ago
A k-NN Based Perception Scheme for Reinforcement Learning
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...
José Antonio Martin H., Javier de Lope Asia...
ICML
2010
IEEE
15 years 21 days ago
Submodular Dictionary Selection for Sparse Representation
We develop an efficient learning framework to construct signal dictionaries for sparse representation by selecting the dictionary columns from multiple candidate bases. By sparse,...
Andreas Krause, Volkan Cevher
SPATIALCOGNITION
2000
Springer
15 years 3 months ago
Inference and Visualization of Spatial Relations
We present an approach to spatial inference which is based on the procedural semantics of spatial relations. In contrast to qualitative reasoning, we do not use discrete symbolic m...
Sylvia Wiebrock, Lars Wittenburg, Ute Schmid, Frit...
WWW
2011
ACM
14 years 6 months ago
A self-training approach for resolving object coreference on the semantic web
An object on the Semantic Web is likely to be denoted with multiple URIs by different parties. Object coreference resolution is to identify “equivalent” URIs that denote the ...
Wei Hu, Jianfeng Chen, Yuzhong Qu