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pro vyhledávání: '"P A, Leandro"'
Since classical machine learning has become a powerful tool for developing data-driven algorithms, quantum machine learning is expected to similarly impact the development of quantum algorithms. The literature reflects a mutually beneficial relations
Externí odkaz:
http://arxiv.org/abs/2412.09486
Publikováno v:
Journal reference: 2023 IEEE 26th International Conference on Intelligent Transportation Systems, pp. 5548-5554, 2023
Collaborative navigation becomes essential in situations of occluded scenarios in autonomous driving where independent driving policies are likely to lead to collisions. One promising approach to address this issue is through the use of Vehicle-to-Ve
Externí odkaz:
http://arxiv.org/abs/2412.08562
Supervised machine learning methods require large-scale training datasets to perform well in practice. Synthetic data has been showing great progress recently and has been used as a complement to real data. However, there is yet a great urge to asses
Externí odkaz:
http://arxiv.org/abs/2412.05466
Contact centers are crucial in shaping customer experience, especially in industries like airlines where they significantly influence brand perception and satisfaction. Despite their importance, the effect of contact center improvements on business m
Externí odkaz:
http://arxiv.org/abs/2412.04860
The origins of Uranus and Neptune are not fully understood. Their inclined rotation axes -- obliquities -- suggest that they experienced giant impacts during their formation histories. Simulations modeling their accretion from giant impacts among ~5
Externí odkaz:
http://arxiv.org/abs/2412.02785
Similarities in the non-mass dependent isotopic composition of refractory elements with the bulk silicate Earth suggest that both the Earth and the Moon formed from the same material reservoir. On the other hand, the Moon's volatile depletion and iso
Externí odkaz:
http://arxiv.org/abs/2412.01361
Autor:
de Souza, Allan M., Maciel, Filipe, da Costa, Joahannes B. D., Bittencourt, Luiz F., Cerqueira, Eduardo, Loureiro, Antonio A. F., Villas, Leandro A.
Federated Learning (FL) is a distributed approach to collaboratively training machine learning models. FL requires a high level of communication between the devices and a central server, thus imposing several challenges, including communication bottl
Externí odkaz:
http://arxiv.org/abs/2411.17833
Estimating quantum partition functions is a critical task in a variety of fields. However, the problem is classically intractable in general due to the exponential scaling of the Hamiltonian dimension $N$ in the number of particles. This paper introd
Externí odkaz:
http://arxiv.org/abs/2411.17816
Layer pruning offers a promising alternative to standard structured pruning, effectively reducing computational costs, latency, and memory footprint. While notable layer-pruning approaches aim to detect unimportant layers for removal, they often rely
Externí odkaz:
http://arxiv.org/abs/2411.14345
Publikováno v:
Integrated Formal Methods, IFM 2024, LNCS 15234 (2025), pp 24-34
TLA+ is a formal specification language used for designing, modeling, documenting, and verifying systems through model checking. Despite significant interest from the research community, knowledge about usage of the TLA+ ecosystem in practice remains
Externí odkaz:
http://arxiv.org/abs/2411.13722