Publications associées à Sensitivity analysis for bottleneck assignment problems

Publications associées (11)

Robust Collaborative Learning with Linear Gradient Overhead

Rachid Guerraoui, Nirupam Gupta, Rafaël Benjamin Pinot, Le Nguyen Hoang, Sadegh Farhadkhani, John Stephan

Collaborative learning algorithms, such as distributed SGD (or D-SGD), are prone to faulty machines that may deviate from their prescribed algorithm because of software or hardware bugs, poisoned data or malicious behaviors. While many solutions have been ...

PLMR2023

Democratizing Machine Learning

Nirupam Gupta, Rafaël Benjamin Pinot, Alexandre David Olivier Maurer

The increasing prevalence of personal devices motivates the design of algorithms that can leverage their computing power, together with the data they generate, in order to build privacy-preserving and effective machine learning models. However, traditional ...

IEEE2022

Reduced representations of complexes, signals, and multifiltrations

Celia Camille Hacker

The field of computational topology has developed many powerful tools to describe the shape of data, offering an alternative point of view from classical statistics. This results in a variety of complex structures that are not always directly amenable for ...

EPFL2022

Automating Algebraic Proof Systems Is NP-Hard

Mika Tapani Göös

We show that algebraic proofs are hard to find: Given an unsatisfiable CNF formula F, it is NP-hard to find a refutation of F in the Nullstellensatz, Polynomial Calculus, or Sherali-Adams proof systems in time polynomial in the size of the shortest such re ...

ASSOC COMPUTING MACHINERY2021

Further development of the RDRA method for the optimal acquisition of data in process integration retrofit projects

Tuong-Van Nguyen

Process Integration techniques are powerful in analysing the energy usage of industrial plants and designing retrofit solutions for increasing their energy efficiency. However they are far from constituting the industrial practice. One primary cause for th ...

ELSEVIER SCI LTD2021

Conditional gradient methods for stochastically constrained convex minimization

Volkan Cevher, Ya-Ping Hsieh, Ahmet Alacaoglu, Maria-Luiza Vladarean

We propose two novel conditional gradient-based methods for solving structured stochastic convex optimization problems with a large number of linear constraints. Instances of this template naturally arise from SDP-relaxations of combinatorial problems, whi ...

2020

i-PI 2.0: A universal force engine for advanced molecular simulations

Michele Ceriotti, Anne-Clémence Corminboeuf, David Mark Wilkins, Bingqing Cheng, Venkat Kapil, Mariana Rossi Carvalho, Riccardo Petraglia, Benjamin Aaron Helfrecht, Robert Horst Meissner

Progress in the atomic-scale modeling of matter over the past decade has been tremendous. This progress has been brought about by improvements in methods for evaluating interatomic forces that work by either solving the electronic structure problem explici ...

ELSEVIER SCIENCE BV2019

Low-Rank Updates And A Divide-And-Conquer Method For Linear Matrix Equations

Daniel Kressner, Stefano Massei

Linear matrix equations, such as the Sylvester and Lyapunov equations, play an important role in various applications, including the stability analysis and dimensionality reduction of linear dynamical control systems and the solution of partial differentia ...

SIAM PUBLICATIONS2019

Dual Coupled Diffusion for Distributed Optimization with Affine Constraints

Ali H. Sayed, Kun Yuan, Sulaiman A S A E Alghunaim

In this work, a distributed multi-agent optimization problem is studied where different subsets of agents are coupled with each other through affine constraints. Moreover, each agent is only aware of its own contribution to the constraints and only knows w ...

IEEE2018

Streaming Robust Submodular Maximization: A Partitioned Thresholding Approach

Volkan Cevher, Slobodan Mitrovic, Ilija Bogunovic, Jakub Tarnawski, Ashkan Norouzi Fard

We study the classical problem of maximizing a monotone submodular function subject to a cardinality constraint k, with two additional twists: (i) elements arrive in a streaming fashion and (ii) m items from the algorithm’s memory might be removed after th ...

2017

Education and management in using especially hazardous chemicals in a research and teaching institution

Thierry Meyer, Jean-Luc Marendaz, Sebastian Brückner

2016