Concept
No free lunch in search and optimization
Publications associées (34)
Optimizing Atomic Layer Deposition Processes with Nanowire-Assisted TEM Analysis
Johann Michler, Ivo Utke, Xavier Maeder
Atomic layer deposition (ALD) is one of the premier methods to synthesize ultra-thin materials on complex surfaces. The technique allows for precise control of the thickness down to single atomic layers, while at the same time providing uniform coverage ev ...
Hoboken2024RMAML: Riemannian meta-learning with orthogonality constraints
Meta-learning is the core capability that enables intelligent systems to rapidly generalize their prior ex-perience to learn new tasks. In general, the optimization-based methods formalize the meta-learning as a bi-level optimization problem, that is a nes ...
ELSEVIER SCI LTD2023Policy-based Exploration of Equilibrium Representations (PEER): A topology grammar for generative conceptual structural design
Design exploration is a creative process that consists of the incremental generation of design candidates. Supported by digital means or not, the process handles the ill-structured nature of design and allows creativity to flourish through diversity of des ...
EPFL2022Dif-MAML: Decentralized Multi-Agent Meta-Learning
Ali H. Sayed, Mert Kayaalp, Stefan Vlaski
The objective of meta-learning is to exploit knowledge obtained from observed tasks to improve adaptation to unseen tasks. Meta-learners are able to generalize better when they are trained with a larger number of observed tasks and with a larger amount of ...
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022Yapa: Accelerated Proximal Algorithm For Convex Composite Problems
Mireille El Gheche, Giovanni Chierchia
Proximal splitting methods are standard tools for nonsmooth optimization. While primal-dual methods have become very popular in the last decade for their flexibility, primal methods may still be preferred for two reasons: acceleration schemes are more effe ...
IEEE2021From Data to Decisions: Distributionally Robust Optimization is Optimal
Daniel Kuhn, Peyman Mohajerin Esfahani
We study stochastic programs where the decision-maker cannot observe the distribution of the exogenous uncertainties but has access to a finite set of independent samples from this distribution. In this setting, the goal is to find a procedure that transfo ...
2020Real-Time Optimization of Interconnected Systems via Modifier Adaptation, with Application to Gas-Compressor Stations
The process industries are characterized by a large number of continuously operating plants, for which optimal operation is of economic and ecological importance.
Many industrial systems can be regarded as an arrangement of several subsystems,
where outp ...
EPFL2018Interior Point Decomposition for Multi-Agent Optimization
Colin Neil Jones, Altug Bitlislioglu, Ivan Pejcic
In this paper we present the application of the interior-point decomposition (IPD) method, which was originally formulated for stochastic programming, to optimization problems involving multiple agents that are coupled through constraints and objectives. I ...
2017A concept of wireless and passive very-high temperature sensor
Paul Muralt, Ramin Matloub Aghdam, Andrea Mazzalai
There is a need for sensors capable operating at temperatures above 1000 degrees C. We describe an innovative sensor that might achieve this goal. The sensor comprises two main elements: a thermocouple and a surface acoustic wave (SAW) strain sensor. The c ...
Amer Inst Physics2017Current Trends in Multidrug Optimization: An Alley of Future Successful Treatment of Complex Disorders
The identification of effective and long-lasting cancer therapies still remains elusive, partially due to patient and tumor heterogeneity, acquired drug resistance, and single-drug dose-limiting toxicities. The use of drug combinations may help to overcome ...
Sage Publications Inc2017