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DAGM
2008
Springer
13 years 9 months ago
Approximate Parameter Learning in Conditional Random Fields: An Empirical Investigation
We investigate maximum likelihood parameter learning in Conditional Random Fields (CRF) and present an empirical study of pseudo-likelihood (PL) based approximations of the paramet...
Filip Korc, Wolfgang Förstner
UAI
2004
13 years 9 months ago
The Minimum Information Principle for Discriminative Learning
Exponential models of distributions are widely used in machine learning for classification and modelling. It is well known that they can be interpreted as maximum entropy models u...
Amir Globerson, Naftali Tishby
ICASSP
2011
IEEE
12 years 11 months ago
Robust adaptive beamforming based on jointly estimating covariance matrix and steering vector
In this paper, a new adaptive beamforming algorithm with joint robustness against covariance matrix uncertainty as well as steering vector mismatch is proposed. First, the theoret...
Yujie Gu, Amir Leshem
ICCV
2009
IEEE
15 years 14 days ago
Tensor completion for estimating missing values in visual data
In this paper we propose an algorithm to estimate missing values in tensors of visual data. The values can be missing due to problems in the acquisition process, or because the ...
Ji Liu, Przemyslaw Musialski, Peter Wonka, Jieping...
PRIB
2009
Springer
209views Bioinformatics» more  PRIB 2009»
14 years 2 months ago
Class Prediction from Disparate Biological Data Sources Using an Iterative Multi-Kernel Algorithm
For many biomedical modelling tasks a number of different types of data may influence predictions made by the model. An established approach to pursuing supervised learning with ...
Yiming Ying, Colin Campbell, Theodoros Damoulas, M...