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ML
2012
ACM
388views Machine Learning» more  ML 2012»
12 years 1 months ago
Statistical analysis of kernel-based least-squares density-ratio estimation
The ratio of two probability densities can be used for solving various machine learning tasks such as covariate shift adaptation (importance sampling), outlier detection (likeliho...
Takafumi Kanamori, Taiji Suzuki, Masashi Sugiyama
ICDM
2008
IEEE
176views Data Mining» more  ICDM 2008»
14 years 7 days ago
Inlier-Based Outlier Detection via Direct Density Ratio Estimation
We propose a new statistical approach to the problem of inlier-based outlier detection, i.e., finding outliers in the test set based on the training set consisting only of inlier...
Shohei Hido, Yuta Tsuboi, Hisashi Kashima, Masashi...
IPMI
2003
Springer
14 years 6 months ago
Bayesian Multimodality Non-rigid Image Registration via Conditional Density Estimation
Abstract. We present a Bayesian multimodality non-rigid image registration method. Since the likelihood is unknown in the general multimodality setting, we use a density estimator ...
Jie Zhang, Anand Rangarajan
CORR
2008
Springer
133views Education» more  CORR 2008»
13 years 5 months ago
Estimating divergence functionals and the likelihood ratio by convex risk minimization
We develop and analyze M-estimation methods for divergence functionals and the likelihood ratios of two probability distributions. Our method is based on a non-asymptotic variatio...
XuanLong Nguyen, Martin J. Wainwright, Michael I. ...
IJPRAI
1998
100views more  IJPRAI 1998»
13 years 5 months ago
Obtaining The Correspondence between Bayesian and Neural Networks
We present in this paper a novel method for eliciting the conditional probability matrices needed for a Bayesian network with the help of a neural network. We demonstrate how we c...
Athena Stassopoulou, Maria Petrou