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» A Privacy Preserving Framework for Gaussian Mixture Models
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ICML
2005
IEEE
14 years 8 months ago
Compact approximations to Bayesian predictive distributions
We provide a general framework for learning precise, compact, and fast representations of the Bayesian predictive distribution for a model. This framework is based on minimizing t...
Edward Snelson, Zoubin Ghahramani
PAMI
2008
109views more  PAMI 2008»
13 years 7 months ago
Likelihood Ratio-Based Biometric Score Fusion
Multibiometric systems fuse information from different sources to compensate for the limitations in performance of individual matchers. We propose a framework for optimal combinati...
Karthik Nandakumar, Yi Chen, Sarat C. Dass, Anil K...
ICASSP
2011
IEEE
12 years 11 months ago
HNM-based MFCC+F0 extractor applied to statistical speech synthesis
Currently, the statistical framework based on Hidden Markov Models (HMMs) plays a relevant role in speech synthesis, while voice conversion systems based on Gaussian Mixture Model...
Daniel Erro, Iñaki Sainz, Eva Navas, Inma H...
CCS
2009
ACM
14 years 2 months ago
CoSP: a general framework for computational soundness proofs
We describe CoSP, a general framework for conducting computational soundness proofs of symbolic models and for embedding these proofs into formal calculi. CoSP considers arbitrary...
Michael Backes, Dennis Hofheinz, Dominique Unruh
CVPR
2012
IEEE
11 years 10 months ago
Light field denoising, light field superresolution and stereo camera based refocussing using a GMM light field patch prior
With the recent availability of commercial light field cameras, we can foresee a future in which light field signals will be as common place as images. Hence, there is an immine...
Kaushik Mitra, Ashok Veeraraghavan