Publications associées à Advancing Distributed AC Optimal Power Flow for Integrated Transmission-Distribution Systems

Publications associées (12)

Global Group Fairness in Federated Learning via Function Tracking

We investigate group fairness regularizers in federated learning, aiming to train a globally fair model in a distributed setting. Ensuring global fairness in distributed training presents unique challenges, as fairness regularizers typically involve probab ...

2025

Relatively Robust Economic Order Quantity with Optimal Laplacian Confidence Intervals

Thomas Alois Weber

The parameters for determining the economic order quantity (EOQ) are often not well known or may change between order cycles in an unpredictable manner. We propose a distribution-free method to determine a relatively robust EOQ that guarantees optimal cost ...

IEEE2025

The Topology of Non-resonant Stellarator Divertors

Christopher Berg Smiet

We apply topological methods to better understand how the magnetic field in the stellarator edge can be diverted away from the confined region. Our primary method is calculating the winding numbers of closed contours, which gives information on the number ...

IOP Publishing Ltd2025

Engineering of stable and functional metalloproteins using evolutionary computation, deep learning and simulation

Simon Leonard Dürr

Metal ions are indispensable cofactors for many proteins and play crucial roles in numerous biological processes, yet the computational design of metalloproteins and the optimization of metal coordination sites poses significant challenges due to the comp ...

EPFL2025

Swift : a modern highly parallel gravity and smoothed particle hydrodynamics solver for astrophysical and cosmological applications

Yves Revaz, Yannick Michael Bahé, Loïc Hausammann, Mladen Ivkovic

Numerical simulations have become one of the key tools used by theorists in all the fields of astrophysics and cosmology. The development of modern tools that target the largest existing computing systems and exploit state-of-the-art numerical methods and ...

2024

Optimal Convex Lifted Sparse Phase Retrieval and PCA With an Atomic Matrix Norm Regularizer

Andrew Duncan Mc Rae

We present novel analysis and algorithms for solving sparse phase retrieval and sparse principal component analysis (PCA) with convex lifted matrix formulations. The key innovation is a new mixed atomic matrix norm that, when used as regularization, promot ...

2023

A Simple LP-Based Approximation Algorithm for the Matching Augmentation Problem

Ola Nils Anders Svensson, Etienne Michel François Bamas, Marina Rebekah Rosie Drygala

The Matching Augmentation Problem (MAP) has recently received significant attention as an important step towards better approximation algorithms for finding cheap 2-edge connected subgraphs. This has culminated in a 5/3-approximation algorithm. However, th ...

SPRINGER INTERNATIONAL PUBLISHING AG2022

Non-Structured DNN Weight Pruning--Is It Beneficial in Any Platform?

Shaokai Ye

Large deep neural network (DNN) models pose the key challenge to energy efficiency due to the significantly higher energy consumption of off-chip DRAM accesses than arithmetic or SRAM operations. It motivates the intensive research on model compression wit ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Evaluation and optimization of novel extraction algorithms for the automatic detection of atrial activations recorded within the pulmonary veins during atrial fibrillation

Jean-Marc Vesin, Etienne Pruvot, Sasan Yazdani, Adrian Luca, Yann Prudat

Background and objective The automated detection of atrial activations (AAs) recorded from intracardiac electrograms (IEGMs) during atrial fibrillation (AF) is challenging considering their various amplitudes, morphologies and cycle length. Activation time ...

BMC2022

An automatized method to determine latencies of motor-evoked potentials under physiological and pathophysiological conditions

Friedhelm Christoph Hummel, Takuya Morishita, Pierre Theopistos Vassiliadis, Andéol Geoffroy Cadic-Melchior, Claudia Bigoni

Background. Latencies of motor evoked potentials (MEPs) can provide insights into the motor neuronal pathways activated by transcranial magnetic stimulation. Notwithstanding its clinical relevance, accurate, unbiased methods to automatize latency detection ...

IOP Publishing Ltd2022

Offshore wind farm wake modelling using deep feed forward neural networks for active yaw control and layout optimisation

Sokratis Anagnostopoulos

Offshore wind farm modelling has been an area of rapidly increasing interest over the last two decades, with numerous analytical as well as computational-based approaches developed, in an attempt to produce designs that improve wind farm efficiency in powe ...

IOP PUBLISHING LTD2022

Design of adaptive structures through energy minimization: extension to tensegrity

Gennaro Senatore, Yafeng Wang

This paper gives a new formulation to design adaptive structures through total energy optimization (TEO). This methodology enables the design of truss as well as tensegrity configurations that are equipped with linear actuators to counteract the effect of ...

2021