Publications associées à Graphe sommet-transitif

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

Martin Jaggi, Thijs Vogels, Hadrien Hendrikx

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

Asymptotics of Cheeger constants and unitarisability of groups

Nicolas Monod, Maria Gerasimova

Given a group Gamma, we establish a connection between the unitarisability of its uniformly bounded representations and the asymptotic behaviour of the isoperimetric constants of Cayley graphs of Gamma for increasingly large generating sets. The connection ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2020

Exponential extinction time of the contact process on finite graphs

Thomas Mountford, Daniel Rodrigues Valesin, Jean-Christophe Mourrat

We study the extinction time tau of the contact process started with full occupancy on finite trees of bounded degree. We show that, if the infection rate is larger than the critical rate for the contact process on Z, then, uniformly over all trees of degr ...

Elsevier Science Bv2016

Boolean logic optimization in majority-inverter graphs

Giovanni De Micheli, Pierre-Emmanuel Julien Marc Gaillardon, Luca Gaetano Amarù

We present a Boolean logic optimization framework based on Majority-Inverter Graph (MIG). An MIG is a directed acyclic graph consisting of three-input majority nodes and regular/complemented edges. Current MIG optimization is supported by a consistent alge ...

2016

Majority-Inverter Graph for FPGA Synthesis

Giovanni De Micheli, Paolo Ienne, Ana Petkovska, Pierre-Emmanuel Julien Marc Gaillardon, Luca Gaetano Amarù, David Novo Bruna

In this paper, we present an FPGA synthesis flow based on Majority-Inverter Graph (MIG). An MIG is a directed acyclic graph consisting of three-input majority nodes and regular/complemented edges. MIG manipulation is supported by a consistent alge ...

2015

Resting-brain functional connectivity predicted by analytic measures of network communication

Jean-Philippe Thiran, Alessandra Griffa, Patric Hagmann, Olaf Sporns

6 The complex relationship between structural and functional connectivity, as measured by noninvasive imaging of the human brain, poses many unresolved challenges and open questions. Here, we apply analytic measures of network communication to the structur ...

National Academy of Sciences2014

Majority-Inverter Graph: A Novel Data-Structure and Algorithms for Efficient Logic Optimization

Giovanni De Micheli, Pierre-Emmanuel Julien Marc Gaillardon, Luca Gaetano Amarù

In this paper, we present Majority-Inverter Graph (MIG), a novel logic representation structure for efficient optimization of Boolean functions. An MIG is a directed acyclic graph consisting of three-input majority nodes and regular/complemented e ...

2014

Zero-temperature Monte Carlo study of the noncoplanar phase of the classical bilinear-biquadratic Heisenberg model on the triangular lattice

Frédéric Mila, Karlo Penc, Sandro Wenzel

We investigate the ground-state properties of the highly degenerate noncoplanar phase of the classical bilinear-biquadratic Heisenberg model on the triangular lattice with Monte Carlo simulations. For that purpose, we introduce an Ising pseudospin represen ...

2013

Degeneracy and ordering of the noncoplanar phase of the classical bilinear-biquadratic Heisenberg model on the triangular lattice

Frédéric Mila, Karlo Penc

We investigate the zero-temperature behavior of the classical Heisenberg model on the triangular lattice in which the competition between exchange interactions of different orders favors a relative angle between neighboring spins Phi is an element of (0,2 ...

2012

Decoding brain states from fMRI connectivity graphs

Dimitri Nestor Alice Van De Ville, Jonas Richiardi

Functional connectivity analysis of fMRI data can reveal synchronised activity between anatomically distinct brain regions. Here, we extract the characteristic connectivity signatures of different brain states to perform classification, allowing us to deco ...

2011