74 citations · 109 across the 7 of their papers we have counts for
8 papers
Learning Planar Ising Models
Jason K. Johnson, Diane Oyen, Michael Chertkov +1
Inference and learning of graphical models are both well-studied problems in statistics and machine learning that have found many applications in science and engineering. However,…
Improved Linear Programming Decoding using Frustrated Cycles
Shrinivas Kudekar, Jason K. Johnson, Misha Chertkov
We consider transmission over a binary-input additive white Gaussian noise channel using low-density parity-check codes. One of the most popular techniques for decoding low-density…
Linear Programming based Detectors for Two-Dimensional Intersymbol Interference Channels
Shrinivas Kudekar, Jason K. Johnson, Michael Chertkov
We present and study linear programming based detectors for two-dimensional intersymbol interference channels. Interesting instances of two-dimensional intersymbol interference cha…
Learning Planar Ising Models
Jason K. Johnson, Praneeth Netrapalli, Michael Chertkov
Inference and learning of graphical models are both well-studied problems in statistics and machine learning that have found many applications in science and engineering. However,…
A Majorization-Minimization Approach to Design of Power Transmission Networks
Jason K. Johnson, Michael Chertkov
We propose an optimization approach to design cost-effective electrical power transmission networks. That is, we aim to select both the network structure and the line conductances…
Orbit-Product Representation and Correction of Gaussian Belief Propagation
Jason K. Johnson, Vladimir Y. Chernyak, Michael Chertkov
We present a new view of Gaussian belief propagation (GaBP) based on a representation of the determinant as a product over orbits of a graph. We show that the GaBP determinant esti…