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» A Privacy Preserving Framework for Gaussian Mixture Models
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CIKM
2006
Springer
14 years 11 days ago
k nearest neighbor classification across multiple private databases
Distributed privacy preserving data mining tools are critical for mining multiple databases with a minimum information disclosure. We present a framework including a general model...
Li Xiong, Subramanyam Chitti, Ling Liu
ICPR
2002
IEEE
14 years 9 months ago
Probabilistic Models for Generating, Modelling and Matching Image Categories
In this paper we present a probabilistic and continuous framework for supervised image category modelling and matching as well as unsupervised clustering of image space into image...
Hayit Greenspan, Shiri Gordon, Jacob Goldberger
CVPR
2005
IEEE
14 years 10 months ago
Subspace Analysis Using Random Mixture Models
In [1], three popular subspace face recognition methods, PCA, Bayes, and LDA were analyzed under the same framework and an unified subspace analysis was proposed. However, since t...
Xiaogang Wang, Xiaoou Tang
UAI
2003
13 years 10 months ago
Bayesian Hierarchical Mixtures of Experts
The Hierarchical Mixture of Experts (HME) is a well-known tree-structured model for regression and classification, based on soft probabilistic splits of the input space. In its o...
Christopher M. Bishop, Markus Svensén
ICASSP
2011
IEEE
13 years 11 days ago
Structured precision modelling with Cholesky Basis Superposition for speech recognition
Structured precision modelling is an important approach to improve the intra-frame correlation modelling of the standard HMM, where Gaussian mixture model with diagonal covariance...
Lei Jia, Kai Yu, Bo Xu