Alexander, Samuel Hibbard, Bill
Published in
Journal of Artificial General Intelligence
In 2011, Hibbard suggested an intelligence measure for agents who compete in an adversarial sequence prediction game. We argue that Hibbard’s idea should actually be considered as two separate ideas: first, that the intelligence of such agents can be measured based on the growth rates of the runtimes of the competitors that they defeat; and second,...
Zhuang, Xincheng Tian, Yang Wang, Haoping Ali, Sofiane Ahmed
This paper proposes a novel Neural Network Adaptive Observer (NNAO) for Nonlinear Systems with Partially and Completely Unknown Dynamics (NSPCUD), subject to variable sampled and delayed output. The method involves designing a neural network observer for partially unknown nonlinear systems with sampled and delayed outputs, using a radial basis func...
Heuillet, Alexandre Tabia, Hedi Arioui, Hichem Youcef-Toumi, Kamal
Differentiable ARchiTecture Search (DARTS) is one of the most trending Neural Architecture Search (NAS) methods. It drastically reduces search cost by resorting to weight-sharing. However, this approach also dramatically reduces the search space, thus excluding potential promising architectures. In this article, we propose D-DARTS, a solution that ...
Piana, Thibault Arzel, Matthieu Aissa El Bey, Abdeldjalil Thomas, Alain
Chatelain, Lucas Vennat, Elsa Tremblay, Nicolas Rousseau, David Gourrier, Aurélien
International audience
Prévost, Clémence Leplat, Valentin
This paper introduces a family of coupled tensor optimization problems for joint super-resolution and unmixing in remote sensing. Using β-divergences allows the proposed methods to account for various noise statistics. A family of simple, efficient and flexible algorithms is proposed, that are capable of solving the two problems at hand. Moreover, ...
Sharp, Christina del Hougne, Philipp Horsley, Simon A. R.
The scattering of light impacts sensing and communication technologies throughout the electromagnetic spectrum. Overcoming the effects of time-varying scattering media is particularly challenging. In this article we introduce a new way to control the propagation of light through dynamic complex media. Our strategy is based on the observation that m...
Alqasir, Hiba Muselet, Damien Ducottet, Christophe
The efficiency of deep neural networks is increasing, and so is the amount of annotated data required for training them. We propose a solution improving the learning process of a classification network with less labeled data. Our approach is to inform the classifier of the elements it should focus on to make its decision by supplying it with some s...
Tapie, Jean Prod'homme, Hugo del Hougne, Philipp
Wireless networks-on-chip (WNoCs) are an enticing complementary interconnect technology for multi-core chips but face severe resource constraints. Being limited to simple on-offkeying modulation, the reverberant nature of the chip enclosure imposes limits on allowed modulation speeds in sight of intersymbol interference, casting doubts on the compe...
Escande, Paul
The anisotropic fractional Brownian field (AFBF) is a non-stationary Gaussian random field which has been used for the modeling of textured images. In this paper, we address the open issue of estimating the functional parameters of this field, namely the topothesy and Hurst functions. We propose an original method which fits the empirical semi-vari...