Publications related to Convergence analysis for sequential Monte Carlo receivers in communications applications

Exploiting the Signal-Leak Bias in Diffusion Models

Sabine Süsstrunk, Radhakrishna Achanta, Mahmut Sami Arpa, Martin Nicolas Everaert, Athanasios Fitsios

There is a bias in the inference pipeline of most diffusion models. This bias arises from a signal leak whose distribution deviates from the noise distribution, creating a discrepancy between training and inference processes. We demonstrate that this signa ...

2024

Functional data analysis with rough sample paths?

Victor Panaretos, Neda Mohammadi Jouzdani

Functional data are typically modeled as sample paths of smooth stochastic processes in order to mitigate the fact that they are often observed discretely and noisily, occasionally irregularly and sparsely. The smoothness assumption is imposed to allow for ...

TAYLOR & FRANCIS LTD2023

Localization errors of the stochastic heat equation

David Jean-Michel Candil

In this thesis, we study the stochastic heat equation (SHE) on bounded domains and on the whole Euclidean space

\R^d.

We confirm the intuition that as the bounded domain increases to the whole space, both solutions become arbitrarily close to one another ...

EPFL2022

On Preconditioning of Decentralized Gradient-Descent When Solving a System of Linear Equations

Nirupam Gupta

This article considers solving an overdetermined system of linear equations in peer-to-peer multiagent networks. The network is assumed to be synchronous and strongly connected. Each agent has a set of local data points, and their goal is to compute a line ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Sensitivity, Noise and Resolution in a B -Modified Foundry-Made ISFET with Miniaturized Reference Electrode for Wearable Point-of-Care Applications

Mihai Adrian Ionescu, Junrui Zhang, Francesco Bellando, Pierpaolo Palestri, Luca Selmi

Ion-sensitive field-effect transistors (ISFETs) form a high sensitivity and scalable class of sensors, compatible with advanced complementary metal-oxide semiconductor (CMOS) processes. Despite many previous demonstrations about their merits as low-power ...

2021

Supersymmetries in nonequilibrium Langevin dynamics

Elisabeth Agoritsas

Stochastic phenomena are often described by Langevin equations, which serve as a mesoscopic model for microscopic dynamics. It has been known since the work of Parisi and Sourlas that reversible (or equilibrium) dynamics present supersymmetries (SUSYs). Th ...

2021

On the Advantage of Coherent LoRa Detection in the Presence of Interference

Andreas Peter Burg, Alexios Konstantinos Balatsoukas Stimming, Orion Afisiadis, Joachim Tobias Tapparel, Sitian Li

It has been shown that the coherent detection of long range (LoRa) signals only provides marginal gains of around 0.7 dB on the additive white Gaussian noise (AWGN) channel. However, ALOHA-based massive Internet-of-Things systems, including LoRa, often ope ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

An Ultra Low-Noise Micropower PPG Sensor

Antonino Caizzone

Nowadays, efficient and remote health monitoring is becoming increasingly important, given both the ageing of population and the combined action of an increase in obesity level and cardiovascular diseases. The healthcare industry is becoming more reliant o ...

EPFL2020

Bits through Time

Elie Najm

In any communication system, there exist two dimensions through which the information at the source becomes distorted before reaching the destination: the noisy channel and time. Messages transmitted through a noisy channel are susceptible to modification ...

EPFL2019

UniXGrad: A Universal, Adaptive Algorithm with Optimal Guarantees for Constrained Optimization

Volkan Cevher, Ali Kavis

We propose a novel adaptive, accelerated algorithm for the stochastic constrained convex optimization setting. Our method, which is inspired by the Mirror-Prox method, \emph{simultaneously} achieves the optimal rates for smooth/non-smooth problems with eit ...

2019

Convergence analysis for sequential Monte Carlo receivers in communications applications

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Exploiting the Signal-Leak Bias in Diffusion Models

Functional data analysis with rough sample paths?

Localization errors of the stochastic heat equation

On Preconditioning of Decentralized Gradient-Descent When Solving a System of Linear Equations

Sensitivity, Noise and Resolution in a B -Modified Foundry-Made ISFET with Miniaturized Reference Electrode for Wearable Point-of-Care Applications

Supersymmetries in nonequilibrium Langevin dynamics

On the Advantage of Coherent LoRa Detection in the Presence of Interference

An Ultra Low-Noise Micropower PPG Sensor

Bits through Time

UniXGrad: A Universal, Adaptive Algorithm with Optimal Guarantees for Constrained Optimization

Localization errors of the stochastic heat equation

Bits through Time

On the Advantage of Coherent LoRa Detection in the Presence of Interference

Functional data analysis with rough sample paths?

Sensitivity, Noise and Resolution in a B -Modified Foundry-Made ISFET with Miniaturized Reference Electrode for Wearable Point-of-Care Applications

An Ultra Low-Noise Micropower PPG Sensor

On Preconditioning of Decentralized Gradient-Descent When Solving a System of Linear Equations

Supersymmetries in nonequilibrium Langevin dynamics

Exploiting the Signal-Leak Bias in Diffusion Models

UniXGrad: A Universal, Adaptive Algorithm with Optimal Guarantees for Constrained Optimization