Publication

Splitting Methods for Distributed Optimization and Control

Related publications (91)

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Augmented Memory: Sample-Efficient Generative Molecular Design with Reinforcement Learning

Philippe Schwaller, Jeff Guo

Sample efficiency is a fundamental challenge in de novo molecular design. Ideally, molecular generative models should learn to satisfy a desired objective under minimal calls to oracles (computational property predictors). This problem becomes more apparen ...

Amer Chemical Soc2024

Augmented Lagrangian Methods for Provable and Scalable Machine Learning

Mehmet Fatih Sahin

Non-convex constrained optimization problems have become a powerful framework for modeling a wide range of machine learning problems, with applications in k-means clustering, large- scale semidefinite programs (SDPs), and various other tasks. As the perfor ...

EPFL2023

Universal and adaptive methods for robust stochastic optimization

Ali Kavis

Within the context of contemporary machine learning problems, efficiency of optimization process depends on the properties of the model and the nature of the data available, which poses a significant problem as the complexity of either increases ad infinit ...

EPFL2023

C-shells: Deployable Gridshells with Curved Beams

Mark Pauly, Francis Julian Panetta, Seiichi Eduardo Suzuki Erazo, Quentin Christian Becker, Yingying Ren, Davide Pellis

We introduce a computational pipeline for simulating and designing C-shells, a new class of planar-to-spatial deployable linkage structures. A C-shell is composed of curved flexible beams connected at rotational joints that can be assembled in a stress-fre ...

2023

Level-set-based Shape Optimization on Soft Magnetic Composites with Isotropy Constraint

Yves Perriard, Adrien Jean-Michel Thabuis, Xiaotao Ren

Soft Magnetic Composites (SMCs) demonstrate excellent potentials for electromagnetic applications. The isotropy is one critical feature in designing the composite. This work presents a shape optimization algorithm for SMCs subject to isotropy and volume co ...

2022

The research community has been making significant progress in hardware implementation, numerical computing and algorithm development for optimization-based control. However, there are two key challenges that still have to be overcome for optimization-base ...

EPFL2021

Modified Joint Channel-and-Data Estimation for One-Bit Massive MIMO

Mahdi Amiri, Saeed Saadatnejad, Mohammadhossein Bahari

Centralized and cloud computing-based network architectures are the promising tracks of future communication systems where a large scale compute power can be virtualized for various algorithms. These architectures rely on high-performance communication lin ...

IEEE2021

Adaptive structures modify their geometry and internal forces through sensing and mechanical actuation in order to maintain optimal performance under changing actions. Previous work has shown that well-conceived adaptive design strategies achieve substanti ...

EPFL2020

This paper introduces a new algorithm for consensus optimization in a multi-agent network, where all agents collaboratively find a minimizer for the sum of their private functions. All decentralized algorithms rely on communications between adjacent nodes. ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Realistic Constrained Multi-Objective Optimization Benchmark Problems from Design

Jürg Alexander Schiffmann, Cyril Picard

Multi-objective optimization is increasingly used in engineering to design new systems and to identify design trade-offs. Yet, design problems often have objective functions and constraints that are expensive and highly non-linear. Combinations of these fe ...

2020