Message-Passing Estimation from Quantized Samples

Preserving communication bandwidth with a gradient coding scheme

Large–scale machine learning involves the communicaiton of gradients, and large models often saturate the communication bandwidth to communicate gradients. I implement an existing scheme, quantized stochastic gradient descent (QSGD) to reduce the communication bandwidth. This requires a distributed architecture and we choose to implement a parameter server that uses the Message Passing Interfac...

LMMSE Estimation and Interpolation of Continuous-Time Signals from Discrete-Time Samples Using Factor Graphs

The factor graph approach to discrete-time linear Gaussian state space models is well developed. The paper extends this approach to continuous-time linear systems / filters that are driven by white Gaussian noise. By Gaussian message passing, we then obtain MAP / MMSE / LMMSE estimates of the input signal, or of the state, or of the output signal from noisy observations of the output signal. Th...

MAP Estimation, Message Passing, and Perfect Graphs

Efficiently finding the maximum a posteriori (MAP) configuration of a graphical model is an important problem which is often implemented using message passing algorithms. The optimality of such algorithms is only well established for singly-connected graphs and other limited settings. This article extends the set of graphs where MAP estimation is in P and where message passing recovers the exac...

A reduced-complexity scheme using message passing for location tracking

This article presents a low-complexity and high-accuracy algorithm using message-passing approach to reduce the computational load of the traditional tracking algorithm for location estimation. In the proposed tracking scheme, a state space model for the location-estimation problem can be divided into many mutual-interaction local constraints based on the inherent message-passing features of fa...

Centralized Estimation of Adhesion Loss in Wheel – Rail System Using Variational Bayes and Variational Message Passing