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pro vyhledávání: '"Gomes, Joao P. P."'
Autor:
Garibaldi, Eduardo, Gomes, João T A
For transitive Markov subshifts over countable alphabets, this note ensures that a dense subclass of locally H\"older continuous potentials admits at most a single periodic probability as a maximizing measure with compact support. We resort to concep
Externí odkaz:
http://arxiv.org/abs/2410.06464
Autor:
de Souza, Daniel Augusto, Nikitin, Alexander, John, ST, Ross, Magnus, Álvarez, Mauricio A., Deisenroth, Marc Peter, Gomes, João P. P., Mesquita, Diego, Mattos, César Lincoln C.
Gaussian processes (GPs) can provide a principled approach to uncertainty quantification with easy-to-interpret kernel hyperparameters, such as the lengthscale, which controls the correlation distance of function values. However, selecting an appropr
Externí odkaz:
http://arxiv.org/abs/2310.11527
Autor:
Hämäläinen, Joonas, Hubermont, Antoine, Souza, Amauri, Mattos, César L. C., Gomes, João P. P., Kärkkäinen, Tommi
Distance-based supervised method, the minimal learning machine, constructs a predictive model from data by learning a mapping between input and output distance matrices. In this paper, we propose new methods and evaluate how their core component, the
Externí odkaz:
http://arxiv.org/abs/2305.05518
Localization is a fundamental enabler technology for many applications, like vehicular networks, IoT, and even medicine. While Global Navigation Satellite Systems solutions offer great performance, they are unavailable in scenarios like indoor or und
Externí odkaz:
http://arxiv.org/abs/2304.05988
This paper addresses target localization with an online active learning algorithm defined by distributed, simple and fast computations at each node, with no parameters to tune and where the estimate of the target position at each agent is asymptotica
Externí odkaz:
http://arxiv.org/abs/2210.09107
Autor:
Soares, Claudia, Gomes, João
Publikováno v:
Signal Processing 185 (2021): 108066
Real-world network applications must cope with failing nodes, malicious attacks, or nodes facing corrupted data - data classified as outliers. Our work addresses these concerns in the scope of the sensor network localization problem where, despite th
Externí odkaz:
http://arxiv.org/abs/2110.00594
Publikováno v:
IEEE Signal Processing Letters 27 (2020): 670-674
Hybrid localization in GNSS-challenged environments using measured ranges and angles is becoming increasingly popular, in particular with the advent of multimodal communication systems. Here, we address the hybrid network localization problem using r
Externí odkaz:
http://arxiv.org/abs/2110.03523
Orbit determination of spacecraft in orbit has been mostly dependent on either GNSS satellite signals or ground station telemetry. Both methods present their limitations, however: GNSS signals can only be used effectively in earth orbit, and ground-b
Externí odkaz:
http://arxiv.org/abs/2109.09186
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