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QEA-QCNN: optimization of quantum convolutional neural network architecture based on quantum evolution
Quantum neural network (QNN) is a research orientation that combines quantum computing and machine learning. It has the potential to solve the...
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New low-rank optimization model and algorithms for spectral compressed sensing
In this paper, we investigate the recovery of an undamped spectrally sparse signal and its spectral components from a set of regularly spaced samples...
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Boundary Stabilization for a Heat-Kelvin-Voigt Unstable Interaction Model, with Control and Partial Observation Localized at the Interface Only
A prototype model for a Fluid–Structure interaction is considered. We aim to stabilize [enhance stability of] the model by having access only to a...
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Clifford-valued linear canonical wave-packet transform and corresponding uncertainty principles
In an effort to express Clifford-valued signals efficiently in time–frequency domain, we introduce the notion of the novel integral transform known...
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Ϝ-Contraction of Hardy–Rogers type in supermetric spaces with applications
This article focuses on studying some fixed-point results via Ϝ -contraction of Hardy–Rogers type in the context of supermetric space and ordered...
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Negative Type and Bi-lipschitz Embeddings into Hilbert Space
The usual theory of negative type (and p -negative type) is heavily dependent on an embedding result of Schoenberg, which states that a metric space...
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Towards robust automated math problem solving: a survey of statistical and deep learning approaches
Automated mathematical problem-solving represents a unique intersection of natural language processing (NLP) and mathematical reasoning, posing...
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Perturbation of least squares problem of dual linear operator in dual-Hilbert spaces
We introduce the dual-Hilbert space and study the basic properties of a dual operator and its generalized inverse on this space. We provide upper...
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On the asymptotic risk of ridge regression with many predictors
This work is concerned with the properties of the ridge regression where the number of predictors p is proportional to the sample size n . Asymptotic...
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Mackey imprimitivity and commuting tuples of homogeneous normal operators
In this semi-expository article, we investigate the relationship between the imprimitivity introduced by Mackey several decades ago and commuting d -...
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Some Sharp Bohr-Type Inequalities for Analytic Functions
This article focuses on the improvement of the classic Bohr’s inequality for bounded analytic functions on the unit disk. We give some sharp versions...
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Random forest classifier for high entropy alloys phase diagnosis
The random forest (RF) algorithm is considered as a powerful statistical classifier that is more popular in other fields but is relatively unknown in...
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Tensor Robust Principal Component Analysis via Non-convex Low-Rank Approximation Based on the Laplace Function
Recently, the tensor robust principal component analysis (TRPCA), aiming to recover the true low-rank tensor from noisy data, has attracted...
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A Generalized Brezis–Lieb Lemma on Graphs and Its Application to Kirchhoff Type Equations
In this paper, with the help of potential function, we extend the classical Brezis–Lieb lemma on Euclidean space to graphs, which can be applied to...
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Incremental concept cognitive learning in dynamic formal contexts based on attribute partial order structure diagram
Partial order formal structure analysis (POFSA) is an emerging theory in the field of concept cognitive learning (CCL). Attribute partial order...
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On a class of Kirchhoff problems with nonlocal terms and logarithmic nonlinearity
In this present paper, we concern investigating nonlinear Kirchhoff-type problems subject to Dirichlet boundary conditions, incorporating nonlocal...
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Sequences of operator algebras converging to odd spheres in the quantum Gromov–Hausdorff distance
Marc Rieffel had introduced the notion of the quantum Gromov–Hausdorff distance on compact quantum metric spaces and found a sequence of matrix...
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Feynman–Kac perturbation of \(C^*\) quantum stochastic flows
The method of Feynman–Kac perturbation of quantum stochastic processes has a long pedigree, with the theory usually developed within the framework of...