Zobrazeno 1 - 10
of 738
pro vyhledávání: '"Carvalho, P. H."'
Recent works have introduced LEAPS and HPRL, systems that learn latent spaces of domain-specific languages, which are used to define programmatic policies for partially observable Markov decision processes (POMDPs). These systems induce a latent spac
Externí odkaz:
http://arxiv.org/abs/2410.12166
In this paper, we present a novel hybrid deep learning model, named ConvLSTMTransNet, designed for time series prediction, with a specific application to internet traffic telemetry. This model integrates the strengths of Convolutional Neural Networks
Externí odkaz:
http://arxiv.org/abs/2409.13179
Autor:
Carvalho, Pedro H.
Given a $\mathfrak{g}$-action on a Poisson manifold $(M, \pi)$ and an equivariant map $J: M \rightarrow \mathfrak{h}^*,$ for $\mathfrak{h}$ a $\mathfrak{g}$-module, we obtain, under natural compatibility and regularity conditions previously considere
Externí odkaz:
http://arxiv.org/abs/2309.07327
Autor:
de Souza, Luciano S., de Carvalho, Jonathan H. A., Santos, Henrique C. T., Ferreira, Tiago A. E.
In this paper, we analyze the application of the Multi-self-loop Lackadaisical Quantum Walk on the hypercube that uses partial phase inversion to search for multiple adjacent marked vertices. We evaluate the influence of the relative position of non-
Externí odkaz:
http://arxiv.org/abs/2305.19614
Autor:
de Souza, Luciano S., de Carvalho, Jonathan H. A., Santos, Henrique C. T., Ferreira, Tiago A. E.
The lackadaisical quantum walk, a quantum analog of the lazy random walk, is obtained by adding a weighted self-loop transition to each state. Impacts of the self-loop weight $l$ on the final success probability in finding a solution make it a key pa
Externí odkaz:
http://arxiv.org/abs/2305.01121
Autor:
Santos, Henrique C. T., de Souza, Luciano S., de Carvalho, Jonathan H. A., Ferreira, Tiago A. E.
The need for computational resources grows as computational algorithms gain popularity in different sectors of the scientific community. This search has stimulated the development of several cloud platforms that abstract the complexity of computation
Externí odkaz:
http://arxiv.org/abs/2301.05770
Quantum computing has been revolutionizing the development of algorithms. However, only noisy intermediate-scale quantum devices are available currently, which imposes several restrictions on the circuit implementation of quantum algorithms. In this
Externí odkaz:
http://arxiv.org/abs/2202.12496
Publikováno v:
IEEE, 2019 8th Brazilian Conference on Intelligent Systems (BRACIS)
This work proposes a computational procedure that uses a quantum walk in a complete graph to train classical artificial neural networks. The idea is to apply the quantum walk to search the weight set values. However, it is necessary to simulate a qua
Externí odkaz:
http://arxiv.org/abs/2109.00128
Publikováno v:
IEEE Transactions on Computers, 13 January 2021
This paper proposes a computational procedure that applies a quantum algorithm to train classical artificial neural networks. The goal of the procedure is to apply quantum walk as a search algorithm in a complete graph to find all synaptic weights of
Externí odkaz:
http://arxiv.org/abs/2108.12448
Publikováno v:
Brazilian Conference on Intelligent Systems: Intelligent Systems pp 249-263, 2021
Adding self-loops at each vertex of a graph improves the performance of quantum walks algorithms over loopless algorithms. Many works approach quantum walks to search for a single marked vertex. In this article, we experimentally address several prob
Externí odkaz:
http://arxiv.org/abs/2108.09399