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143
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CVPR
2005
IEEE
16 years 6 months ago
WaldBoost - Learning for Time Constrained Sequential Detection
: In many computer vision classification problems, both the error and time characterizes the quality of a decision. We show that such problems can be formalized in the framework of...
Jan Sochman, Jiri Matas
GECCO
2006
Springer
173views Optimization» more  GECCO 2006»
15 years 7 months ago
Pareto-coevolutionary genetic programming classifier
The conversion and extension of the Incremental ParetoCoevolution Archive algorithm (IPCA) into the domain of Genetic Programming classifier evolution is presented. In order to ac...
Michal Lemczyk, Malcolm I. Heywood
148
Voted
ICML
2006
IEEE
16 years 4 months ago
Convex optimization techniques for fitting sparse Gaussian graphical models
We consider the problem of fitting a large-scale covariance matrix to multivariate Gaussian data in such a way that the inverse is sparse, thus providing model selection. Beginnin...
Onureena Banerjee, Laurent El Ghaoui, Alexandre d'...
MLMI
2004
Springer
15 years 9 months ago
Towards Predicting Optimal Fusion Candidates: A Case Study on Biometric Authentication Tasks
Combining multiple information sources, typically from several data streams is a very promising approach, both in experiments and to some extend in various real-life applications. ...
Norman Poh, Samy Bengio
145
Voted
ICML
2010
IEEE
15 years 5 months ago
Gaussian Processes Multiple Instance Learning
This paper proposes a multiple instance learning (MIL) algorithm for Gaussian processes (GP). The GP-MIL model inherits two crucial benefits from GP: (i) a principle manner of lea...
Minyoung Kim, Fernando De la Torre