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» Alignment by Maximization of Mutual Information
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KBS
2006
150views more  KBS 2006»
14 years 11 months ago
Clusterer ensemble
Ensemble methods that train multiple learners and then combine their predictions have been shown to be very effective in supervised learning. This paper explores ensemble methods ...
Zhi-Hua Zhou, Wei Tang
JMLR
2008
159views more  JMLR 2008»
14 years 11 months ago
Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies
When monitoring spatial phenomena, which can often be modeled as Gaussian processes (GPs), choosing sensor locations is a fundamental task. There are several common strategies to ...
Andreas Krause, Ajit Paul Singh, Carlos Guestrin
CAISE
2004
Springer
15 years 5 months ago
Why we understand each other: the role of the context
This short paper addresses the problem of mutual understanding from an anthropomorphic point of view, highlighting the underlying basic mechanisms and principles. Then the paper ex...
G. Andrighetto, Pierluigi Assogna
IPMI
2007
Springer
16 years 17 days ago
Geometry Driven Volumetric Registration
In this paper, we propose a novel method for the registration of volumetric images of the brain that attempts to maximize the overlap of cortical folds. In order to achieve this, r...
Gheorghe Postelnicu, Lilla Zöllei, Rahul Desi...
CVPR
2005
IEEE
16 years 1 months ago
Infomax Boosting
In this paper, we described an efficient feature pursuit scheme for boosting. The proposed method is based on the infomax principle, which seeks optimal feature that achieves maxi...
Siwei Lyu