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» Learning the Common Structure of Data
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UAI
2008
15 years 5 months ago
Causal discovery of linear acyclic models with arbitrary distributions
An important task in data analysis is the discovery of causal relationships between observed variables. For continuous-valued data, linear acyclic causal models are commonly used ...
Patrik O. Hoyer, Aapo Hyvärinen, Richard Sche...
WEBI
2004
Springer
15 years 9 months ago
Mining Local Data Sources For Learning Global Cluster Models
— Distributed data mining has recently caught a lot of attention as there are many cases where pooling distributed data for mining is probibited, due to either huge data volume o...
Chak-Man Lam, Xiaofeng Zhang, William Kwok-Wai Che...
126
Voted
ICIP
2009
IEEE
15 years 1 months ago
An automatic Structure-Aware image extrapolation applied to error concealment
A novel framework for spatially estimating unknown image data is presented. Common applications include inpainting, concealment of transmission errors, prediction in video coding,...
Haricharan Lakshman, Patrick Ndjiki-Nya, Martin K&...
ATAL
2005
Springer
15 years 9 months ago
Multi-agent reward analysis for learning in noisy domains
In many multi agent learning problems, it is difficult to determine, a priori, the agent reward structure that will lead to good performance. This problem is particularly pronoun...
Adrian K. Agogino, Kagan Tumer
129
Voted
NIPS
2004
15 years 5 months ago
Boosting on Manifolds: Adaptive Regularization of Base Classifiers
In this paper we propose to combine two powerful ideas, boosting and manifold learning. On the one hand, we improve ADABOOST by incorporating knowledge on the structure of the dat...
Balázs Kégl, Ligen Wang