Privacy-Preserving Belief Propagation and Sampling

13 years 6 months ago

Download www.cis.upenn.edu

We provide provably privacy-preserving versions of belief propagation, Gibbs sampling, and other local algorithms — distributed multiparty protocols in which each party or vertex learns only its ﬁnal local value, and absolutely nothing else.

Michael Kearns, Jinsong Tan, Jennifer Wortman

Real-time Traffic

Gibbs Sampling | Information Technology | Multiparty Protocols | NIPS 2007 | ﬁnal Local Value |

claim paper

» Sequential Stratified Sampling Belief Propagation for Multiple Targets Tracking

» Efficient Nonparametric Belief Propagation with Application to Articulated Body Tracking

» RealTime 3D Articulated Pose Tracking using Particle Filters Interacting through Belief Pr...

» Nonparametric Belief Propagation

» A Gaussian Belief Propagation Solver for Large Scale Support Vector Machines

» Learning to Estimate Human Pose with Data Driven Belief Propagation

» Dense Photometric Stereo Using Tensorial Belief Propagation

» Guiding belief propagation using domain knowledge for proteinstructure determination

Post Info
More Details (n/a)

Added	30 Oct 2010
Updated	30 Oct 2010
Type	Conference
Year	2007
Where	NIPS
Authors	Michael Kearns, Jinsong Tan, Jennifer Wortman

Comments (0)

Sciweavers

Privacy-Preserving Belief Propagation and Sampling

Gibbs Sampling | Information Technology | Multiparty Protocols | NIPS 2007 | ﬁnal Local Value |

Explore & Download

Productivity Tools

Document Tools

Image Tools

Sciweavers