Publication

Feedback topology and XOR-dynamics in Boolean networks with varying input structure

Publications associées (31)

Privatized graph federated learning

Federated learning is a semi-distributed algorithm, where a server communicates with multiple dispersed clients to learn a global model. The federated architecture is not robust and is sensitive to communication and computational overloads due to its one-m ...

SPRINGER2023

Power variations in fractional Sobolev spaces for a class of parabolic stochastic PDEs

Robert Dalang, Carsten Hao Ye Chong

We consider a class of parabolic stochastic PDEs on bounded domains D c Rd that includes the stochastic heat equation but with a fractional power gamma of the Laplacian. Viewing the solution as a process with values in a scale of fractional Sobolev spaces ...

INT STATISTICAL INST2023

Equilibria in Network Constrained Energy Markets

Leonardo Massai

We study an energy market composed of producers who compete to supply energy to different markets and want to maximize their profits. The energy market is modeled by a graph representing a constrained power network where nodes represent the markets and lin ...

Elsevier2023

Bootstrapping traceless symmetric O(N) scalars

Alessandro Vichi, Maria Refinetti, Marten Jan Reehorst

We use numerical bootstrap techniques to study correlation functions of traceless sym-metric tensors of O(N) with two indices ti j. We obtain upper bounds on operator dimen-sions for all the relevant representations and several values of N. We discover sev ...

SCIPOST FOUNDATION2023

Discovering Influencers in Opinion Formation Over Social Graphs

Ali H. Sayed, Mert Kayaalp, Valentina Shumovskaia, Mert Cemri

The adaptive social learning paradigm helps model how networked agents are able to form opinions on a state of nature and track its drifts in a changing environment. In this framework, the agents repeatedly update their beliefs based on private observation ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Graph neural networks for dynamic modeling of roller bearings

Olga Fink, Vinay Sharma

Machine learning has paved the way for the real-time monitoring of complex infrastructure and industrial systems. However, purely data-driven methods have not been able to learn the underlying dynamics and generalize them to operating conditions that have ...

PHM Society2023

Better Trees for Santa Claus

Etienne Michel François Bamas, Lars Rohwedder

We revisit the problem max-min degree arborescence, which was introduced by Bateni et al. [STOC'09] as a central special case of the general Santa Claus problem, which constitutes a notorious open question in approximation algorithms. In the former problem ...

Assoc Computing Machinery2023

Scalable maximal subgraph mining with backbone-preserving graph convolutions

Karl Aberer, Quoc Viet Hung Nguyen, Thành Tâm Nguyên, Thanh Trung Huynh

Maximal subgraph mining is increasingly important in various domains, including bioinformatics, genomics, and chemistry, as it helps identify common characteristics among a set of graphs and enables their classification into different categories. Existing ...

ELSEVIER SCIENCE INC2023

Beyond Spectral Gap: The Role of the Topology in Decentralized Learning

Thijs Vogels, Hadrien Hendrikx, Martin Jaggi

In data-parallel optimization of machine learning models, workers collaborate to improve their estimates of the model: more accurate gradients allow them to use larger learning rates and optimize faster. In the decentralized setting, in which workers commu ...

Microtome Publishing2023

Scalable Computation of Dynamic Flow Problems via Multimarginal Graph-Structured Optimal Transport

Axel Ringh, Yiqiang Chen, Isabel Haasler

In this work, we develop a new framework for dynamic network flow pro-blems based on optimal transport theory. We show that the dynamic multicommodity minimum-cost network flow problem can be formulated as a multimarginal optimal transport problem, where t ...

2023

Possible restoration of particle-hole symmetry in the 5/2-quantized Hall state at small magnetic field

Frédéric Mila, Loïc Jean Pierre Herviou

Motivated by the experimental observation of a quantized 5/2 thermal conductance at filling nu = 5/2, a result incompatible with both the Pfaffian and the anti-Pfaffian states, we have pushed the expansion of the effective Hamiltonian of the 5/2-quantized ...

AMER PHYSICAL SOC2023