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ICML
2008
IEEE
16 years 5 months ago
Topologically-constrained latent variable models
In dimensionality reduction approaches, the data are typically embedded in a Euclidean latent space. However for some data sets this is inappropriate. For example, in human motion...
Raquel Urtasun, David J. Fleet, Andreas Geiger, Jo...
154
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COLT
2005
Springer
15 years 10 months ago
Generalization Error Bounds Using Unlabeled Data
We present two new methods for obtaining generalization error bounds in a semi-supervised setting. Both methods are based on approximating the disagreement probability of pairs of ...
Matti Kääriäinen
ICML
2008
IEEE
16 years 5 months ago
Training SVM with indefinite kernels
Similarity matrices generated from many applications may not be positive semidefinite, and hence can't fit into the kernel machine framework. In this paper, we study the prob...
Jianhui Chen, Jieping Ye
CORR
2011
Springer
203views Education» more  CORR 2011»
14 years 12 months ago
Guided Data Repair
In this paper we present GDR, a Guided Data Repair framework that incorporates user feedback in the cleaning process to enhance and accelerate existing automatic repair techniques...
Mohamed Yakout, Ahmed K. Elmagarmid, Jennifer Nevi...
JMLR
2012
13 years 7 months ago
A Stick-Breaking Likelihood for Categorical Data Analysis with Latent Gaussian Models
The development of accurate models and efficient algorithms for the analysis of multivariate categorical data are important and longstanding problems in machine learning and compu...
Mohammad Emtiyaz Khan, Shakir Mohamed, Benjamin M....