The formalism of probabilistic graphical models provides a unifying framework for capturing
complex dependencies among random variables, and building large-scale multivariate …

We present a novel message passing algorithm for approximating the MAP problem in
graphical models. The algorithm is similar in structure to max-product but unlike max-product …

A novel class of bit-flip** (BF) algorithm for decoding low-density parity-check (LDPC)
codes is presented. The proposed algorithms, which are referred to as gradient descent bit …

When binary linear error-correcting codes are used over symmetric channels, a relaxed
version of the maximum likelihood decoding problem can be stated as a linear program …

Inference problems in graphical models can be represented as a constrained optimization of
a free-energy function. In this paper, we treat both forms of probabilistic inference, estimating …

Linear programming (LP) decoding for low-density parity-check codes was introduced by
Feldman et al. and has been shown to have theoretical guarantees in several regimes …

Linear program (LP) decoding has become increasingly popular for error-correcting codes
due to its simplicity and promising performance. Low-complexity and efficient iterative …

Low-complexity and high-performance low-density parity-check (LDPC) decoders are highly
demanded in various modern communication and storage systems. In this paper, a novel …

Alternating direction method of multipliers (ADMM) is an efficient implementation of linear
programming (LP) decoding for low-density parity-check (LDPC) codes. By adding penalty …

In this paper, we propose a new linear programming formulation for the decoding of general
linear block codes. Different from the original formulation given by Feldman, the number of …