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It has become commonplace to use complex computer models to predict outcomes in regions where data does not exist. Typically these models need to be calibrated and validated using some experimental data, which often consists of multiple…

Data-parallel SGD is the de facto algorithm for distributed optimization, especially for large scale machine learning. Despite its merits, communication bottleneck is one of its persistent issues. Most compression schemes to alleviate this…

Neural and Evolutionary Computing · Computer Science 2024-02-07 Ashok Vardhan Makkuva , Marco Bondaschi , Thijs Vogels , Martin Jaggi , Hyeji Kim , Michael C. Gastpar

We explore the relation between the techniques of statistical mechanics and information theory for assessing the performance of channel coding. We base our study on a framework developed by Gallager in {\em IEEE Trans. Inform. Theory} {\bf…

Information Theory · Computer Science 2009-11-13 Yoshiyuki Kabashima

We present Selective Non-Gaussian Refinement (SNGR), a SLAM framework that augments iSAM2 with targeted nested sampling on windows where Gaussian approximations are likely to fail. We detect such regions using the condition number of joint…

Robotics · Computer Science 2026-04-27 Anushka Kulkarni , Sarthak Dubey

This paper considers the problem of closed-loop identification of linear scalar systems with Gaussian process noise, where the system input is determined by a deterministic state feedback policy. The regularized least-square estimate (LSE)…

Systems and Control · Electrical Eng. & Systems 2020-03-30 Ali Reza Pedram , Takashi Tanaka

We introduce a novel approach to error correction decoding in the presence of additive alpha-stable noise, which serves as a model of interference-limited wireless systems. In the absence of modifications to decoding algorithms, treating…

Information Theory · Computer Science 2024-10-31 Charles Wiame , Ken R. Duffy , Muriel Médard

Although for a number of semilinear stochastic wave equations existence and uniqueness results for corresponding solution processes are known from the literature, these solution processes are typically not explicitly known and numerical…

Probability · Mathematics 2021-11-02 Ladislas Jacobe de Naurois , Arnulf Jentzen , Timo Welti

In this work, we consider efficient maximum-likelihood decoding of linear block codes for small-to-moderate block lengths. The presented approach is a branch-and-bound algorithm using the cutting-plane approach of Zhang and Siegel (IEEE…

Information Theory · Computer Science 2014-04-29 Michael Helmling , Eirik Rosnes , Stefan Ruzika , Stefan Scholl

The next generation of space- and ground-based facilities promise to reveal an entirely new picture of the gravitational wave sky: thousands of galactic and extragalactic binary signals, as well as stochastic gravitational wave backgrounds…

General Relativity and Quantum Cosmology · Physics 2024-07-03 James Alvey , Uddipta Bhardwaj , Valerie Domcke , Mauro Pieroni , Christoph Weniger

In this paper, we study a remote source coding scenario in which binary phase shift keying (BPSK) modulation sources are corrupted by additive white Gaussian noise (AWGN). An intermediate node, such as a relay, receives these observations…

Information Theory · Computer Science 2024-05-14 Yi Song , Kai Wan , Zhenyu Liao , Giuseppe Caire

Gallager-type error-correcting codes that nearly saturate Shannon's bound are constructed using insight gained from mapping the problem onto that of an Ising spin system. The performance of the suggested codes is evaluated for different…

Disordered Systems and Neural Networks · Physics 2009-10-31 Ido Kanter , David Saad

Mixed noise, composed of white Gaussian noise (WGN) and impulsive noise (IN), appears in numerous communication scenarios and can severely degrade system performance. In this paper, we optimize the transmitted constellation under mixed…

Signal Processing · Electrical Eng. & Systems 2025-09-09 Tianfu Qi , Jun Wang

In this paper we propose a new design criterion and a new class of unitary signal constellations for differential space-time modulation for multiple-antenna systems over Rayleigh flat-fading channels with unknown fading coefficients.…

Information Theory · Computer Science 2008-05-12 Xinjia Chen , Kemin Zhou , Jorge Aravena

A recent line of work has focused on the use of low-density generator matrix (LDGM) codes for lossy source coding. In this paper, wedevelop a generic technique for deriving lower bounds on the rate-distortion functions of binary linear…

Information Theory · Computer Science 2008-08-18 A. G. Dimakis , M. J. Wainwright , K. Ramchandran

The design of block codes for short information blocks (e.g., a thousand or less information bits) is an open research problem that is gaining relevance thanks to emerging applications in wireless communication networks. In this paper, we…

Information Theory · Computer Science 2019-03-12 Mustafa Cemil Coşkun , Giuseppe Durisi , Thomas Jerkovits , Gianluigi Liva , William Ryan , Brian Stein , Fabian Steiner

To fully unlock the scientific potential of upcoming gravitational wave (GW) interferometers, numerical relativity (NR) simulation accuracy will need to be greatly enhanced. We present three infrastructure-agnostic improvements to the…

General Relativity and Quantum Cosmology · Physics 2024-09-19 Zachariah B. Etienne

Linear Least Squares is a very well known technique for parameter estimation, which is used even when sub-optimal, because of its very low computational requirements and the fact that exact knowledge of the noise statistics is not required.…

Signal Processing · Electrical Eng. & Systems 2017-11-01 Michael Krikheli , Amir Leshem

This paper presents a novel unified performance analysis of Space-Time Block Codes (STBCs) operating in the Multiple Input Multiple Output (MIMO) network and subjected to generalized shadowed fading and noise scenarios. Specifically, we…

Information Theory · Computer Science 2016-08-02 Ehab Salahat , Ali Hakam

The variance reduction class of algorithms including the representative ones, SVRG and SARAH, have well documented merits for empirical risk minimization problems. However, they require grid search to tune parameters (step size and the…

Machine Learning · Computer Science 2020-06-11 Bingcong Li , Lingda Wang , Georgios B. Giannakis

This paper proposes a new framework to compute finite-horizon safety guarantees for discrete-time piece-wise affine systems with stochastic noise of unknown distributions. The approach is based on a novel approach to synthesise a stochastic…

Systems and Control · Electrical Eng. & Systems 2023-09-12 Frederik Baymler Mathiesen , Licio Romao , Simeon C. Calvert , Alessandro Abate , Luca Laurenti