Zobrazeno 1 - 10
of 52
pro vyhledávání: '"Robu, Bogdan"'
Publikováno v:
AAMAS '23: Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems
This paper addresses the problem of integrating local guide policies into a Reinforcement Learning agent. For this, we show how to adapt existing algorithms to this setting before introducing a novel algorithm based on a noisy policy-switching proced
Externí odkaz:
http://arxiv.org/abs/2402.13930
Autor:
Daoudi, Paul, Mavkov, Bojan, Robu, Bogdan, Prieur, Christophe, Witrant, Emmanuel, Barlier, Merwan, Santos, Ludovic Dos
Publikováno v:
2024 IEEE Conference on Control Technology and Applications (CCTA)
This paper presents a learning-based control strategy for non-linear throttle valves with an asymmetric hysteresis, leading to a near-optimal controller without requiring any prior knowledge about the environment. We start with a carefully tuned Prop
Externí odkaz:
http://arxiv.org/abs/2402.13654
Publikováno v:
Proceedings of the the 33rd International Joint Conference on Artificial Intelligence (IJCAI 2024)
Off-dynamics Reinforcement Learning (ODRL) seeks to transfer a policy from a source environment to a target environment characterized by distinct yet similar dynamics. In this context, traditional RL agents depend excessively on the dynamics of the s
Externí odkaz:
http://arxiv.org/abs/2312.15474
In this study we focus on the diagnosis of Parkinson's Disease (PD) based on electroencephalogram (EEG) signals. We propose a new approach inspired by the functioning of the brain that uses the dynamics, frequency and temporal content of EEGs to extr
Externí odkaz:
http://arxiv.org/abs/2210.11624
Autor:
Zhao, Zilong, Birke, Robert, Han, Rui, Robu, Bogdan, Bouchenak, Sara, Mokhtar, Sonia Ben, Chen, Lydia Y.
Classification algorithms have been widely adopted to detect anomalies for various systems, e.g., IoT, cloud and face recognition, under the common assumption that the data source is clean, i.e., features and labels are correctly set. However, data c
Externí odkaz:
http://arxiv.org/abs/2103.10824
Publikováno v:
In Chinese Journal of Traumatology July 2024
Convolutional Neural Network (CNN) has become the most used method for image classification tasks. During its training the learning rate and the gradient are two key factors to tune for influencing the convergence speed of the model. Usual learning r
Externí odkaz:
http://arxiv.org/abs/2003.09503
Convolutional neural networks (CNNs) are commonly used for image classification tasks, raising the challenge of their application on data flows. During their training, adaptation is often performed by tuning the learning rate. Usual learning rate str
Externí odkaz:
http://arxiv.org/abs/1911.07710
Autor:
Zhao, Zilong, Birke, Robert, Han, Rui, Robu, Bogdan, Bouchenak, Sara, Mokhtar, Sonia Ben, Chen, Lydia Y.
Classification algorithms have been widely adopted to detect anomalies for various systems, e.g., IoT, cloud and face recognition, under the common assumption that the data source is clean, i.e., features and labels are correctly set. However, data c
Externí odkaz:
http://arxiv.org/abs/1911.04383
Publikováno v:
In Engineering Applications of Artificial Intelligence November 2023 126 Part B