The authors carry out numerical experiments with regard to the Monte Carlo integration method,using as input the pseudorandom vectors that are generated by the algorithm proposed in[Mok,C.P.,Pseudorandom Vector Genera...
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The authors carry out numerical experiments with regard to the Monte Carlo integration method,using as input the pseudorandom vectors that are generated by the algorithm proposed in[Mok,C.P.,Pseudorandom Vector Generation Using Elliptic Curves and Applications to Wiener Processes,Finite Fields and Their Applications,85,2023,102129],which is based on the arithmetic theory of elliptic curves over finite *** consider integration in the following two cases:The case of Lebesgue measure on the unit hypercube[0,1]d,and as well as the case of Wiener *** the case of Wiener measure,the construction gives discrete time simulation of an independent sequence of standard Wiener processes,which is then used for the numerical evaluation of Feynman-Kac formulas.
作者：
Tarbă, NicolaeIrimescu, Ionela N.Pleavă, Ana M.Scarlat, Eugen N.Mihăilescu, MonaDoctoral School
Computer Science and Engineering Department Faculty of Automatic Control and Computers National University of Science and Technology POLITEHNICA Bucharest Romania Applied Sciences Doctoral School
National University of Science and Technology POLITEHNICA Bucharest Romania CAMPUS Research Center
National University of Science and Technology POLITEHNICA Bucharest Romania Physics Dept
National University of Science and Technology POLITEHNICA Bucharest Romania Physics Dept
Research Center for Applied Sciences in Engineering National University of Science and Technology POLITEHNICA Bucharest Romania
We introduce a method to evaluate the similarities between classes of objects based on the confusion matrices coming from the multi-class machine learning (ML) predictors that operate in the vector space generated by ...
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We present a faithful geometric picture for genuine tripartite entanglement of discrete, continuous, and hybrid quantum systems. We first find that the triangle relation Ei|jkα≤Ej|ikα+Ek|ijα holds for all subaddit...
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We present a faithful geometric picture for genuine tripartite entanglement of discrete, continuous, and hybrid quantum systems. We first find that the triangle relation Ei|jkα≤Ej|ikα+Ek|ijα holds for all subadditive bipartite entanglement measure E, all permutations under parties i,j,k, all α∈[0,1], and all pure tripartite states. Then, we rigorously prove that the nonobtuse triangle area, enclosed by side Eα with 0<α≤1/2, is a measure for genuine tripartite entanglement. Finally, it is significantly strengthened for qubits that given a set of subadditive and nonsubadditive measures, some state is always found to violate the triangle relation for any α>1, and the triangle area is not a measure for any α>1/2. Our results pave the way to study discrete and continuous multipartite entanglement within a unified framework.
The simultaneous existence of motion blur and defocus blur constitutes the mixed blur, which is a great challenge to image deblurring. Therefore, it is necessary to establish the blur model and estimate blur parameter...
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Unsupervised feature selection attempts to select a small number of discriminative features from original high-dimensional data and preserve the intrinsic data structure without using data labels. As an unsupervised l...
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Unsupervised feature selection attempts to select a small number of discriminative features from original high-dimensional data and preserve the intrinsic data structure without using data labels. As an unsupervised learning task, most previous methods often use a coefficient matrix for feature reconstruction or feature projection, and a certain similarity graph is widely utilized to regularize the intrinsic structure preservation of original data in a new feature space. However, a similarity graph with poor quality could inevitably afect the final results. In addition, designing a rational and efective feature reconstruction/projection model is not easy. In this paper, we introduce a novel and efective unsupervised feature selection method via multiple graph fusion and feature weight learning（MGF2WL） to address these issues. Instead of learning the feature coefficient matrix, we directly learn the weights of diferent feature dimensions by introducing a feature weight matrix, and the weighted features are projected into the label space. Aiming to exploit sufficient relation of data samples, we develop a graph fusion term to fuse multiple predefined similarity graphs for learning a unified similarity graph, which is then deployed to regularize the local data structure of original data in a projected label space. Finally, we design a block coordinate descent algorithm with a convergence guarantee to solve the resulting optimization problem. Extensive experiments with sufficient analyses on various datasets are conducted to validate the efficacy of our proposed MGF2WL.
This paper initiates the formal study of attribute-based encryption within the framework of SM9,the Chinese national Cryptography Standard for Identity-Based Cryptography, by presenting two new faulttolerant identity-...
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This paper initiates the formal study of attribute-based encryption within the framework of SM9,the Chinese national Cryptography Standard for Identity-Based Cryptography, by presenting two new faulttolerant identity-based encryption(FIBE) schemes. Our first scheme uses the same private-key/ciphertext structure as the original SM9 algorithm and operates in a small attribute universe. As a result, it can be effectively and smoothly integrated into the information systems using SM9. In the random oracle model,we prove that our scheme is ciphertext-indistinguishable against fuzzy selective-identity and chosen-plaintext attacks under the(k + 3)-DBDHI assumption. Our second design is a large universe FIBE scheme based on SM9 that is ciphertext-indistinguishable against chosen-plaintext attacks in the random oracle model under the(f, g)-GDDHE assumption. Finally, we compare the communication and computing costs of our schemes to those of other classical ones. The comparison shows that our schemes have comparable performance as others. We believe that our findings will accelerate the applications of SM9 in modern information systems such as cloud computing and blockchain.
This study addresses the parameter identification problem in a system of time-dependent quasi-linear partial differential equations(PDEs).Using the integral equation method,we prove the uniqueness of the inverse probl...
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This study addresses the parameter identification problem in a system of time-dependent quasi-linear partial differential equations(PDEs).Using the integral equation method,we prove the uniqueness of the inverse problem in nonlinear ***,using the method of successive approximations,we develop a novel iterative algorithm to estimate sorption *** stability results of the algorithm are proven under both a priori and a posteriori stopping rules.A numerical example is given to show the efficiency and robustness of the proposed new approach.
In this work, a novel methodological approach to multi-attribute decision-making problems is developed and the notion of Heptapartitioned Neutrosophic Set Distance Measures (HNSDM) is introduced. By averaging the Pent...
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In this paper,we propose a variable metric method for unconstrained multiobjective optimization problems(MOPs).First,a sequence of points is generated using different positive definite matrices in the generic *** is p...
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In this paper,we propose a variable metric method for unconstrained multiobjective optimization problems(MOPs).First,a sequence of points is generated using different positive definite matrices in the generic *** is proved that accumulation points of the sequence are Pareto critical ***,without convexity assumption,strong convergence is established for the proposed ***,we use a common matrix to approximate the Hessian matrices of all objective functions,along which a new nonmonotone line search technique is proposed to achieve a local superlinear convergence ***,several numerical results demonstrate the effectiveness of the proposed method.
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