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» Learning in the Presence of Inaccurate Information
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ICML
2007
IEEE
14 years 8 months ago
Robust multi-task learning with t-processes
Most current multi-task learning frameworks ignore the robustness issue, which means that the presence of "outlier" tasks may greatly reduce overall system performance. ...
Shipeng Yu, Volker Tresp, Kai Yu
CCS
2009
ACM
14 years 2 months ago
Learning your identity and disease from research papers: information leaks in genome wide association study
Genome-wide association studies (GWAS) aim at discovering the association between genetic variations, particularly single-nucleotide polymorphism (SNP), and common diseases, which...
Rui Wang, Yong Fuga Li, XiaoFeng Wang, Haixu Tang,...
KDD
2012
ACM
281views Data Mining» more  KDD 2012»
11 years 9 months ago
Active spectral clustering via iterative uncertainty reduction
Spectral clustering is a widely used method for organizing data that only relies on pairwise similarity measurements. This makes its application to non-vectorial data straightforw...
Fabian L. Wauthier, Nebojsa Jojic, Michael I. Jord...
CIE
2007
Springer
14 years 1 months ago
Input-Dependence in Function-Learning
In the standard model of inductive inference, a learner gets as input the graph of a function, and has to discover (in the limit) a program for the function. In this paper, we cons...
Sanjay Jain, Eric Martin, Frank Stephan
IIE
2007
91views more  IIE 2007»
13 years 7 months ago
New Media and Open and Distance Learning: New challenges for Education in a Knowledge Society
The “digital society” provides not only with new technology, but also with new concepts. Information plays a central role and becomes a valuable good, but knowledge cannot be r...
Bernard Cornu