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Concept

Méthode hill-climbing

Publications associées (23)

Novel Ordering-based Approaches for Causal Structure Learning in the Presence of Unobserved Variables

We propose ordering-based approaches for learning the maximal ancestral graph (MAG) of a structural equation model (SEM) up to its Markov equivalence class (MEC) in the presence of unobserved variables. Existing ordering-based methods in the literature rec ...

Association for the Advancement of Artificial Intelligence (AAAI)2023

Enriching the Computational Toolbox for Organocatalysis

Simone Gallarati

Organocatalysis has evolved significantly over the last decades, becoming a pillar of synthetic chemistry, but traditional theoretical approaches based on quantum mechanical computations to investigate reaction mechanisms and provide rationalizations of ca ...

EPFL2023

Dual-function engineering to construct ultra-stable anodes for potassium-ion hybrid capacitors: N, O-doped porous carbon spheres

Kangning Zhao, Yanan Chen

Heteroatom doping engineering is deemed to be an adoptable strategy to boost the potassium (K) storage performance of carbonaceous materials. The inevitable issue for this strategy lies in the huge volume expansion originated from the large radius of K+. I ...

Elsevier2022

Micro-addition of Fe in highly alloyed Cu-Ti alloys to improve both formability and strength

Roland Logé, Cyril Cayron, Baptiste Thomas Jean Rouxel

Cu-Be alloys provide excellent electrical and mechanical properties, but present serious health hazards during manufacturing. Among alternative alloys, the Cu-Ti system has the highest yield strength; however, Ti cannot be easily solutionized at concentrat ...

ELSEVIER SCI LTD2022

Stochastic Second-Order Methods Improve Best-Known Sample Complexity of SGD for Gradient-Dominated Function

Patrick Thiran, Negar Kiyavash, Saber Salehkaleybar

We study the performance of Stochastic Cubic Regularized Newton (SCRN) on a class of functions satisfying gradient dominance property with

1\le\alpha\le2

which holds in a wide range of applications in machine learning and signal processing. This conditio ...

NeurIPS2022

Memory of Motion for Initializing Optimization in Robotics

Teguh Santoso Lembono

Many robotics problems are formulated as optimization problems. However, most optimization solvers in robotics are locally optimal and the performance depends a lot on the initial guess. For challenging problems, the solver will often get stuck at poor loc ...

EPFL2022

Optimization of multi-group energy structures for diffusion analyses of sodium-cooled fast reactors assisted by simulated annealing - Part I: Methodology demonstration

Konstantin Mikityuk, Vincenzo Anthony Di Nora

This study presents an approach to the selection of optimal energy group structures for multi-group nodal diffusion analyses of Sodium-cooled Fast Reactor cores. The goal is to speed up calculations, particularly in transient calculations, while maintainin ...

2021

Active Improvement of Control Policies with Bayesian Gaussian Mixture Model

Sylvain Calinon, Noémie Laure Gwendoline Jaquier, Emmanuel Pignat, Hakan Girgin

Learning from demonstration (LfD) is an intuitive framework allowing non-expert users to easily (re-)program robots. However, the quality and quantity of demonstrations have a great influence on the generalization performances of LfD approaches. In this pa ...

IEEE2020

Walkman: A Communication-Efficient Random-Walk Algorithm for Decentralized Optimization

Ali H. Sayed, Kun Yuan

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

Optimum design of low environmental impact structures through component reuse

Jan Friedrich Georg Brütting

Load-bearing systems (structures) in buildings and infrastructure contribute to a significant share of adverse environmental impacts (EI) because of resource- and energy-intensive fabrication. A currently overlooked circular economy strategy to reduce EI i ...

EPFL2020

Efficient Greedy Coordinate Descent for Composite Problems

Martin Jaggi, Sebastian Urban Stich, Sai Praneeth Reddy Karimireddy, Anastasiia Koloskova

Coordinate descent with random coordinate selection is the current state of the art for many large scale optimization problems. However, greedy selection of the steepest coordinate on smooth problems can yield convergence rates independent of the dimension ...

2019

Enforcing Model Adequacy in Real-Time Optimization via Dedicated Parameter Adaptation

Dominique Bonvin, Martand Singhal

Iterative real-time optimization schemes that employ modifier adaptation add bias and gradient correction terms to the model that is used for optimization. These affine corrections lead to meeting the first-order necessary conditions of optimality of the p ...

ELSEVIER SCIENCE BV2018

Hybrid Cyclicity: Combining The Benefits Of Cyclic And Non-Cyclic Timetables

Michel Bierlaire, Mohammad Yousef Maknoon, Shadi Sharif Azadeh, Tomas Robenek

We propose a new type of timetable that would combine both the regularity of the cyclic timetables and the flexibility of the non-cyclic ones. In order to do so, several combinations of the two timetables are considered. The regularity is incorporated in t ...

Pergamon-Elsevier Science Ltd2017

Smooth Primal-Dual Coordinate Descent Algorithms for Nonsmooth Convex Optimization

Volkan Cevher, Quoc Tran Dinh, Ahmet Alacaoglu

We propose a new randomized coordinate descent method for a convex optimization template with broad applications. Our analysis relies on a novel combination of four ideas applied to the primal-dual gap function: smoothing, acceleration, homotopy, and coord ...

2017

Current Trends in Multidrug Optimization: An Alley of Future Successful Treatment of Complex Disorders

Patrycja Nowak-Sliwinska, Andrea Brett Gasser

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

Simulated Annealing in Optimization of Energy Production in a Water Supply Network

Anton Schleiss, Mário Jorge Rodrigues Pereira Da Franca, Irene Almeida Samora

In water supply systems, the potential exists for micro-hydropower that uses the pressure excess in the networks to produce electricity. However, because urban drinking water networks are complex systems in which flows and pressure vary constantly, identif ...

Springer Verlag2016

Towards large-scale commercialization of fuel cells : robust design optimization considering dimensional uncertainties in the flow distributors

Thierry Mikaël Cornu

The present and future challenges that humanity is facing regarding consumption and supply of energy constitute the context of this research. The technology in which we are interested is the fuel cell, mainly because of its high efficiency for the conversi ...

EPFL2016

An Incremental Anytime Algorithm for Multi-Objective Query Optimization

Christoph Koch, Immanuel Trummer

Query plans offer diverse tradeoffs between conflicting cost metrics such as execution time, energy consumption, or execution fees in a multi-objective scenario. It is convenient for users to choose the desired cost tradeoff in an interactive process, dyna ...

2015

Fixed-structure LPV Discrete-time Controller Design with Induced l2-Norm and H2 Performance

Alireza Karimi, Zlatko Emedi

A new method for the design of fixed-structure dynamic output-feedback Linear Parameter Varying (LPV) controllers for discrete-time LPV systems with bounded scheduling parameter variations is presented. Sufficient conditions for the stability, $\mathscr{H} ...

2015

Further study on iterative control loop for aberration correction in imaging systems with single mode fibre aperture

An iterative control system was designed for compensation of wavefront aberration utilizing a micromachined deformable mirror through simulated annealing algorithm. 37 elements within a deformable mirror are controlled individually in a closed-loop to maxi ...

Natl Inst Optoelectronics2013