Publications associées à A positive combinatorial formula for symplectic Kostka-Foulkes polynomials I: Rows

Scalable constrained optimization

Modern optimization is tasked with handling applications of increasingly large scale, chiefly due to the massive amounts of widely available data and the ever-growing reach of Machine Learning. Consequently, this area of research is under steady pressure t ...

EPFL2024

Learning to Remove Cuts in Integer Linear Programming

Volkan Cevher, Grigorios Chrysos, Efstratios Panteleimon Skoulakis

Cutting plane methods are a fundamental approach for solving integer linear programs (ILPs). In each iteration of such methods, additional linear constraints (cuts) are introduced to the constraint set with the aim of excluding the previous fractional opti ...

2024

Bootstrapping smooth conformal defects in Chern-Simons-matter theories

Amit Sever, Barak Gabai

The expectation value of a smooth conformal line defect in a CFT is a conformal invariant functional of its path in space-time. For example, in large N holographic theories, these fundamental observables are dual to the open-string partition function in Ad ...

Springer Nature2024

Primal-Dual Contextual Bayesian Optimization for Control System Online Optimization with Time-Average Constraints

Colin Neil Jones, Yuning Jiang, Wenjie Xu, Bratislav Svetozarevic

This paper studies the problem of online performance optimization of constrained closed-loop control systems, where both the objective and the constraints are unknown black-box functions affected by exogenous time-varying contextual disturbances. A primal- ...

IEEE2023

Simulating intra-household interactions for in- and out-of-home activity scheduling

Michel Bierlaire, Timothy Michael Hillel, Negar Rezvany

Various interactions, time arrangements, and constraints exist for individuals scheduling their day as a member of a household, which affect their in-home as well as out-of-home activity schedule. However, the existing activity-based models are mostly base ...

Pergamon-Elsevier Science Ltd2023

Quality-Constrained Encoding Optimization for Omnidirectional Video Streaming

Pascal Frossard, Roberto Gerson De Albuquerque Azevedo, Chaofan He

Omnidirectional video streaming is usually implemented based on the representations of tiles, where the tiles are obtained by splitting the video frame into several rectangular areas and each tile is converted into multiple representations with different r ...

Ieee-Inst Electrical Electronics Engineers Inc2023

Studies on EU-DEMO 3D coils requirements and conceptual design for error field correction and plasma control

Pierluigi Bruzzone, Hartmut Zohm, Leonardo Pigatto

This work presents the initial studies on the requirements for the design of 3D coils on EU-DEMO. The use of 3D coils in present machines includes two main purposes: the first one is the Error Field Correction (EFC). The EFC aims at minimizing the intrinsi ...

Elsevier Science Sa2023

Model Predictive Control for Multi-Agent Systems under Limited Communication and Time-Varying Network Topology

Melanie Nicole Zeilinger, Danilo Saccani

In control system networks, reconfiguration of the controller when agents are leaving or joining the network is still an open challenge, in particular when operation constraints that depend on each agent's behavior must be met. Drawing our motivation from ...

IEEE2023

Unsupervised Visual Entity Abstraction towards 2D and 3D Compositional Models

Beril Besbinar

Object-centric learning has gained significant attention over the last years as it can serve as a powerful tool to analyze complex scenes as a composition of simpler entities. Well-established tasks in computer vision, such as object detection or instance ...

EPFL2022

Efficient methods for the operation of active distribution networks in unsymmetric and uncertain states

Sherif Alaa Salaheldin Fahmy

The increasing penetration of stochastic renewable distributed generation, energy storage systems and novel loads (e.g. electric-vehicles (EVs)) in active-distribution-networks (ADNs) or microgrids has triggered the need to develop real-time (e.g. minutes ...

EPFL2022

Finding stationary points on bounded-rank matrices: a geometric hurdle and a smooth remedy

Nicolas Boumal

We consider the problem of provably finding a stationary point of a smooth function to be minimized on the variety of bounded-rank matrices. This turns out to be unexpectedly delicate. We trace the difficulty back to a geometric obstacle: On a nonsmooth se ...

SPRINGER HEIDELBERG2022

Algebraic and Boolean Optimization Methods for AQFP Superconducting Circuits

Giovanni De Micheli, Eleonora Testa, Heinz Riener, Siang-Yun Lee

Adiabatic quantum-flux-parametron (AQFP) circuits are a family of superconducting electronic (SCE) circuits that have recently gained growing interest due to their low-energy consumption, and may serve as alternative technology to overcome the down-scaling ...

IEEE2021

Automated Design: A Journey Across Modelling, Optimization, and Education

Cyril Picard

Machine intelligence greatly impacts almost all domains of our societies. It is profoundly changing the field of mechanical engineering with new technical possibilities and processes. The education of future engineers also needs to adapt in terms of techni ...

EPFL2021

Heightening of Very High Gravity Dams: The Case Study of the Grande Dixence

Giovanni De Cesare, Pedro Filipe De Almeida Manso, Basile Clerc

Heightening very high gravity dams is one of the solutions considered as part of the energy transition and to mitigate the effects of climate change. The paper presents a stepwise approach to assess the potential for dam heightening and its impact on the h ...

Springer, Cham2020

On the asymptotic behavior of the solutions to parabolic variational inequalities

Maria Colombo

We consider various versions of the obstacle and thin-obstacle problems, we interpret them as variational inequalities, with non-smooth constraint, and prove that they satisfy a new constrained Lojasiewicz inequality. The difficulty lies in the fact that, ...

2020

Constraint-aware neural networks for Riemann problems

Jan Sickmann Hesthaven, Deep Ray

Neural networks are increasingly used in complex (data-driven) simulations as surrogates or for accelerating the computation of classical surrogates. In many applications physical constraints, such as mass or energy conservation, must be satisfied to obtai ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2020

Realizability of planar point embeddings from angle measurements

Frederike Dümbgen, Adam James Scholefield, Majed El Helou

Localization of a set of nodes is an important and a thoroughly researched problem in robotics and sensor networks. This paper is concerned with the theory of localization from inner-angle measurements. We focus on the challenging case where no anchor loca ...

IEEE2020

Definition Of A Transparent Constraint-Based Modeling And Simulation Layer For The Management Of Complex Systems

Marina Zapater Sancho, Kevin Henares Vilaboa, José Luis Risco Martin

Modeling and Simulation (M&S) is one of the most multifaceted topics present today in both industry and academia. However, we are involved in a new M&S paradigm. Systems are becoming more complex and new simulation needs arise and have to be studied. As a ...

IEEE2019

Joint Learning of Semantic Alignment and Object Landmark Detection

Seungryong Kim

Convolutional neural networks (CNNs) based approaches for semantic alignment and object landmark detection have improved their performance significantly. Current efforts for the two tasks focus on addressing the lack of massive training data through weakly ...

IEEE2019

Evaluation of feasibility and costs of alternative magnetic divertor configurations for DEMO

Holger Reimerdes, Seungkyu Ha

The European roadmap to the realisation of fusion energy has identified a number of technological and scientific challenges towards the development of a DEMO reactor. Mission 2 'Heat-exhaust systems' includes the investigation of alternative divertor confi ...

ELSEVIER SCIENCE SA2019