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 ...
— 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...
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&...
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...
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...