Publications associées à MILP-based discrete sizing and topology optimization of truss structures: new formulation and benchmarking

Publications associées (18)

Optimal Control under Uncertainty: From Regret Minimization to Distributional Robustness

Recent years have witnessed a growing integration of automatic control into a wide range of cyber-physical systems, including electrical grids and autonomous transportation networks. These systems operate in uncertain and dynamic environments, exhibit comp ...

EPFL2025

Product complexity management enabled by a model-based approach

Dimitrios Kyritsis

As contemporary engineered systems become more interdependent, there is a growing need to manage their system complexity. However, system complexity only exists as implicit and heterogeneous information. This situation makes it difficult to obtain and anal ...

2025

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

Anastasiia Koloskova

Distributed learning is the key for enabling training of modern large-scale machine learning models, through parallelising the learning process. Collaborative learning is essential for learning from privacy-sensitive data that is distributed across various ...

EPFL2024

Efficient Algorithms for a Class of Stochastic Hidden Convex Optimization and Its Applications in Network Revenue Management

Yifan Hu

We study a class of stochastic nonconvex optimization in the form of min(x is an element of X) F(x) := E-xi[f (phi(x, xi))], that is, F is a composition of a convex function f and a random function phi. Leveraging an (implicit) convex reformulation via a v ...

INFORMS2024

The Frontier of Intractability for EFX with Two Agents

Alexandros Paul Hollender

We consider the problem of sharing a set of indivisible goods among agents in a fair manner, namely such that the allocation is envy-free up to any good (EFX). We focus on the problem of computing an EFX allocation in the two-agent case and characterize th ...

Springer International Publishing Ag2023

Editorial Issue 34.2

Daniel Thalmann

WILEY2023

Robotic Assembly of Integrally-Attached Timber Plate Structures: From Computational Design to Automated Construction

Nicolas Henry Pierre Louis Rogeau

The digitization of timber construction, the emergence of engineered wood products, and the urgent need to drastically reduce buildings' environmental impact have given a rebirth to wood as a construction material. On the one hand, increasing the use of ti ...

EPFL2023

On Linear Optimization over Wasserstein Balls

Daniel Kuhn, Wolfram Wiesemann

Wasserstein balls, which contain all probability measures within a pre-specified Wasserstein distance to a reference measure, have recently enjoyed wide popularity in the distributionally robust optimization and machine learning communities to formulate an ...

2022

Spatial Isolation Implies Zero Knowledge Even in a Quantum World

Alessandro Chiesa

Zero knowledge plays a central role in cryptography and complexity. The seminal work of Ben-Or et al. (STOC 1988) shows that zero knowledge can be achieved unconditionally for any language in NEXP, as long as one is willing to make a suitable physical assu ...

ASSOC COMPUTING MACHINERY2022

GarNet++: Improving Fast and Accurate Static 3D Cloth Draping by Curvature Loss

Pascal Fua, Mathieu Salzmann, Shaifali Parashar, Victor Constantin, Erhan Gündogdu

In this paper, we tackle the problem of static 3D cloth draping on virtual human bodies. We introduce a two-stream deep network model that produces a visually plausible draping of a template cloth on virtual 3D bodies by extracting features from both the b ...

2022

Perturbative construction of mean-field equations in extensive-rank matrix factorization and denoising

Lenka Zdeborová, Florent Gérard Krzakala

Factorization of matrices where the rank of the two factors diverges linearly with their sizes has many applications in diverse areas such as unsupervised representation learning, dictionary learning or sparse coding. We consider a setting where the two fa ...

2022

Neural System Level Synthesis: Learning over All Stabilizing Policies for Nonlinear Systems

Giancarlo Ferrari Trecate, Luca Furieri, Clara Lucía Galimberti

We address the problem of designing stabilizing control policies for nonlinear systems in discrete-time, while minimizing an arbitrary cost function. When the system is linear and the cost is convex, the System Level Synthesis (SLS) approach offers an effe ...

IEEE2022

Algebraic Homotopy Interleaving Distance

Nicolas Michel Berkouk

The theory of persistence, which arises from topological data analysis, has been intensively studied in the one-parameter case both theoretically and in its applications. However, its extension to the multi-parameter case raises numerous difficulties, wher ...

SPRINGER INTERNATIONAL PUBLISHING AG2021

PARSINLU: A Suite of Language Understanding Challenges for Persian

Rabeeh Karimi Mahabadi

Despite the progress made in recent years in addressing natural language understanding (NLU) challenges, the majority of this progress remains to be concentrated on resource-rich languages like English. This work focuses on Persian language, one of the wid ...

2021

An Adaptive IoT Network Security Situation Prediction Model

Jiyong Zhang

With the rapid development of the Internet of things (IoT) technology, how to effectively predict the network security situation of the IoT has become particularly important. It is difficult to quantify the IoT network situation due to a large number of hi ...

SPRINGER2021

Joint Segmentation and Path Classification of Curvilinear Structures

Pascal Fua, Mateusz Kozinski, Agata Justyna Mosinska

Detection of curvilinear structures in images has long been of interest. One of the most challenging aspects of this problem is inferring the graph representation of the curvilinear network. Most existing delineation approaches first perform binary segment ...

2020

Development and verification of pin-by-pin homogenized simplified transport solver Tortin for PWR core analysis

Andreas Pautz, Petra Mala

Currently, the pin-by-pin homogenized solvers are a very active research field as they can, unlike the nodal codes, directly predict the local power, while requiring significantly less computational resources than the heterogeneous transport codes. This pa ...

2020

Advanced Machine Learning Techniques for Self-Interference Cancellation in Full-Duplex Radios

Andreas Peter Burg, Andreas Toftegaard Kristensen

In-band full-duplex systems allow for more efficient use of temporal and spectral resources by transmitting and receiving information at the same time and on the same frequency. However, this creates a strong self-interference signal at the receiver, makin ...

IEEE2019