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» Learning Mixtures of Gaussians
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ICASSP
2011
IEEE
12 years 12 months ago
Blind beamformer for constant modulus signals based on relevance vector machine
The blind beamforming method for constant modulus (CM) signals based on relevance vector machine (RVM) is proposed. The proposed beamforming method is obtained by incorporating th...
Kyuho Hwang, Sooyong Choi
JAIR
2008
135views more  JAIR 2008»
13 years 8 months ago
On Similarities between Inference in Game Theory and Machine Learning
In this paper, we elucidate the equivalence between inference in game theory and machine learning. Our aim in so doing is to establish an equivalent vocabulary between the two dom...
Iead Rezek, David S. Leslie, Steven Reece, Stephen...
AII
1992
14 years 8 days ago
Learning from Multiple Sources of Inaccurate Data
Most theoretical models of inductive inference make the idealized assumption that the data available to a learner is from a single and accurate source. The subject of inaccuracies ...
Ganesh Baliga, Sanjay Jain, Arun Sharma
CVPR
2008
IEEE
14 years 10 months ago
Max Margin AND/OR Graph learning for parsing the human body
We present a novel structure learning method, Max Margin AND/OR Graph (MM-AOG), for parsing the human body into parts and recovering their poses. Our method represents the human b...
Long Zhu, Yuanhao Chen, Yifei Lu, Chenxi Lin, Alan...
ECML
2001
Springer
14 years 21 days ago
Learning of Variability for Invariant Statistical Pattern Recognition
In many applications, modelling techniques are necessary which take into account the inherent variability of given data. In this paper, we present an approach to model class speciï...
Daniel Keysers, Wolfgang Macherey, Jörg Dahme...