Title
Algebraically-Initialized Expectation Maximization For Header-Free Communication
Abstract
Towards low-latency communication for short-packet transmission, this paper tackles the problem of shuffled linear regression for large-scale wireless sensor networks with header-free communication by using results from algebraic geometry as well as an alternating optimization scheme. The shuffled linear regression problem is to solve a linear system with shuffled entries of the right hand side vector. However, solving the shuffled linear system requires high computational cost. The key idea of our approach is to eliminate the shuffled structure via symmetric polynomials, which leads to a system of polynomial equations. Considering one of the solutions of the resulting polynomial system as an initialization to the Expectation Maximization algorithm, WC propose the Algebraically-initialized Expectation Maximization algorithm. Computational experiments with synthetic data show that our proposed algorithm is extensively efficient, and it perfornis well even with noise.
Year
DOI
Venue
2019
10.1109/icassp.2019.8682683
2019 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
Keywords
Field
DocType
Header-free communication, shuffled linear regression, permuted linear model, symmetric polynomials, expectation maximization, algebraic geometry
Mathematical optimization,Polynomial,Linear system,Expectation–maximization algorithm,Computer science,System of polynomial equations,Synthetic data,Header,Initialization,Symmetric polynomial
Conference
ISSN
Citations 
PageRank 
1520-6149
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Liangzu Peng112.04
Xuming Song221.10
Manolis C. Tsakiris3509.79
Hayoung Choi433.81
Laurent Kneip543632.31
Yuanming Shi665953.58