activity
20082016
most citedGraphLab: A New Framework For Parallel Machine Learning

440 citations · 1.4k across the 24 of their papers we have counts for

collaborators
Showing 2009Show all

7 papers · 1 filter

cs.IT2009★ 1 cited

Fault Identification via Non-parametric Belief Propagation

Danny Bickson, Dror Baron, Alex T. Ihler +2

We consider the problem of identifying a pattern of faults from a set of noisy linear measurements. Unfortunately, maximum a posteriori probability estimation of the fault pattern…

cs.IT2009★ 3 cited

Distributed Sensor Selection using a Truncated Newton Method

Danny Bickson, Danny Dolev

We propose a new distributed algorithm for computing a truncated Newton method, where the main diagonal of the Hessian is computed using belief propagation. As a case study for thi…

cs.NI2009

A Statistical Approach to Performance Monitoring in Soft Real-Time Distributed Systems

Danny Bickson, Gidon Gershinsky, Ezra N. Hoch +1

Soft real-time applications require timely delivery of messages conforming to the soft real-time constraints. Satisfying such requirements is a complex task both due to the volatil…

cs.IT2009★ 19 cited

Fixing Convergence of Gaussian Belief Propagation

Jason K. Johnson, Danny Bickson, Danny Dolev

Gaussian belief propagation (GaBP) is an iterative message-passing algorithm for inference in Gaussian graphical models. It is known that when GaBP converges it converges to the co…

cs.IT2009★ 5 cited

A Low Density Lattice Decoder via Non-Parametric Belief Propagation

Danny Bickson, Alexander T. Ihler, Danny Dolev

The recent work of Sommer, Feder and Shalvi presented a new family of codes called low density lattice codes (LDLC) that can be decoded efficiently and approach the capacity of the…

cs.NI2009★ 3 cited

A Hybrid Multicast-Unicast Infrastructure for Efficient Publish-Subscribe in Enterprise Networks

Danny Bickson, Ezra N. Hoch, Nir Naaman +1

One of the main challenges in building a large scale publish-subscribe infrastructure in an enterprise network, is to provide the subscribers with the required information, while m…