Publications associées à Algorithme

Frequency-Domain Non-intrusive Greedy Model Order Reduction Based on Minimal Rational Approximation

We present a technique for Model Order Reduction (MOR) of frequency-domain problems relying on rational interpolation of vector-valued functions. The selection of the sample points is carried out adaptively according to a greedy procedure. We describe seve ...

SPRINGER INTERNATIONAL PUBLISHING AG2021

Knapsack and Subset Sum with Small Items

Adam Teodor Polak, Lars Rohwedder

Knapsack and Subset Sum are fundamental NP-hard problems in combinatorial optimization. Recently there has been a growing interest in understanding the best possible pseudopolynomial running times for these problems with respect to various parameters. In t ...

Schloss Dagstuhl -- Leibniz-Zentrum für Informatik2021

The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective

Naman Goel, Amit Sharma

Training datasets for machine learning often have some form of missingness. For example, to learn a model for deciding whom to give a loan, the available training data includes individuals who were given a loan in the past, but not those who were not. This ...

ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE2021

Cluster-and-Conquer: When Randomness Meets Graph Locality

Anne-Marie Kermarrec, Olivier Ruas

K-Nearest-Neighbors (KNN) graphs are central to many emblematic data mining and machine-learning applications. Some of the most efficient KNN graph algorithms are incremental and local: they start from a random graph, which they incrementally improve by tr ...

IEEE COMPUTER SOC2021

Learning convergence prediction of astrobots in multi-object spectrographs

Denis Gillet, Jean-Paul Richard Kneib, Matin Macktoobian, Francesco Basciani

Astrobot swarms are used to capture astronomical signals to generate the map of the observable universe for the purpose of dark energy studies. The convergence of each swarm in the course of its coordination has to surpass a particular threshold to yield a ...

2021

Toward a remote assessment of walking bout and speed: application in patients with multiple sclerosis

Kamiar Aminian, Farzin Dadashi, Benoît Mariani, Arash Atrsaei

Gait speed as a powerful biomarker of mobility is mostly assessed in controlled environments, e.g. in the clinic. With wearable inertial sensors, gait speed can be estimated in an objective manner. However, most of the previous works have validated the gai ...

2021

Pareto-like sequential sampling heuristic for global optimisation

Katrin Beyer, Mahmoud S. M. Shaqfa

In this paper, we propose a simple global optimisation algorithm inspired by Pareto’s principle. This algorithm samples most of its solutions within prominent search domains and is equipped with a self-adaptive mechanism to control the dynamic tightening o ...

2021

Yapa: 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 ...

IEEE2021

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Algorithme

Frequency-Domain Non-intrusive Greedy Model Order Reduction Based on Minimal Rational Approximation

Knapsack and Subset Sum with Small Items

The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective

Cluster-and-Conquer: When Randomness Meets Graph Locality

Learning convergence prediction of astrobots in multi-object spectrographs

Toward a remote assessment of walking bout and speed: application in patients with multiple sclerosis

Variational Monte Carlo Calculations of A

Pareto-like sequential sampling heuristic for global optimisation

Mixed Nash Equilibria in the Adversarial Examples Game

Yapa: Accelerated Proximal Algorithm For Convex Composite Problems

Graph Chatbot

Chattez avec Graph Search

Frequency-Domain Non-intrusive Greedy Model Order Reduction Based on Minimal Rational Approximation

Learning convergence prediction of astrobots in multi-object spectrographs

The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective

Knapsack and Subset Sum with Small Items

Pareto-like sequential sampling heuristic for global optimisation

Mixed Nash Equilibria in the Adversarial Examples Game

Cluster-and-Conquer: When Randomness Meets Graph Locality

Yapa: Accelerated Proximal Algorithm For Convex Composite Problems

Variational Monte Carlo Calculations of A

Toward a remote assessment of walking bout and speed: application in patients with multiple sclerosis