We show how a preselection of hidden variables can be used to efficiently train generative models with binary hidden variables. The approach is based on Expectation Maximization (...
In this paper, we present a new evaluation approach for missing data techniques (MDTs) where the efficiency of those are investigated using listwise deletion method as reference....
Seliz G. Karadogan, Letizia Marchegiani, Lars Kai ...
Multi-instance (MI) learning is a variant of supervised learning where labeled examples consist of bags (i.e. multi-sets) of feature vectors instead of just a single feature vecto...
This paper presents a general method for segmenting a vector valued sequence into an unknown number of subsequences where all data points from a subsequence can be represented wit...
Bundle ajustment is used to obtain accurate visual reconstructions by minimizing the reprojection error. The coordinate frame ambiguity, or more generality the gauge freedoms, has...