Concept

Optimisation par essaims particulaires

Publications associées (296)

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RECA: A Multi-Task Deep Reinforcement Learning-Based Recommender System for Co-Optimizing Energy, Comfort and Air Quality in Commercial Buildings

We present the design and implementation of RECA, a novel human-centric recommender system for co-optimizing energy consumption, comfort and air quality in commercial buildings. Existing works generally optimize these objectives separately, or by only cont ...

Association for Computing Machinery2023

Governance framework for autonomous and cognitive digital twins in agile supply chains

Cognitive Digital twins (CDT) are Digital Twins with cognition capabilities and ensure a proper monitoring and optimization of a specific asset's behaviour. In the context of supply chains, there are different entities involved from assets, processes, up t ...

ELSEVIER2023

Gradient-Based Learning of Discrete Structured Measurement Operators for Signal Recovery

Jonathan Paul Sauder

Countless signal processing applications include the reconstruction of signals from few indirect linear measurements. The design of effective measurement operators is typically constrained by the underlying hardware and physics, posing a challenging and of ...

2022

On the Scalability of Vision-based Drone Swarms in the Presence of Occlusions

Dario Floreano, Fabian Maximilian Schilling, Enrica Soria

Vision-based drone swarms have recently emerged as a promising alternative to address the fault-tolerance and flexibility limitations of centralized and communication-based aerial collective systems. Although most vision-based control algorithms rely on th ...

2022

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This work presents an optimization framework to aggregate the power and energy flexibilities in an interconnected power distribution systems. The aggregation framework is used to compute the day-ahead dispatch plans of multiple and interconnected distribut ...

2022

Byzantine Machine Learning Made Easy By Resilient Averaging of Momentums

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

Byzantine resilience emerged as a prominent topic within the distributed machine learning community. Essentially, the goal is to enhance distributed optimization algorithms, such as distributed SGD, in a way that guarantees convergence despite the presence ...

PMLR2022

Swarms of flying robots in unknown environments

Enrica Soria

An optimal planning algorithm enables swarms of flying robots to explore unknown environments autonomously and safely. ...

AMER ASSOC ADVANCEMENT SCIENCE2022

In this paper, we study the compression of a target two-layer neural network with N nodes into a compressed network with M < N nodes. More precisely, we consider the setting in which the weights of the target network are i.i.d. sub-Gaussian, and we minimiz ...

IEEE2022

Recently, it has been shown that, in spite of the significant performance of deep neural networks in different fields, those are vulnerable to adversarial examples. In this paper, we propose a gradient-based adversarial attack against transformer-based tex ...

IEEE2022

The Canopy Pavilion: A lightweight shading structure using a deployable auxetic linkage membrane

Mark Pauly, Dieter Dietz, Florin Isvoranu, Arthur François Blanc, Tian Chen, Etienne Bouleau

We present the Canopy Pavilion, a lightweight shading structure for a social gathering space. The shading surface is realized as a tensioned auxetic linkage membrane, composed of two double-curved anticlastic layers separated by a compression pole. The mem ...

2022