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A novel deep high-level concept-mining jointing hashing model for unsupervised cross-modal retrieval

High-Confidence computing 2025年第2期5卷

作者： Dong, Chun-Ru Zhang, Jun-Yan Zhang, Feng Hua, Qiang Xu, Dachuan Hebei Key Laboratory of Machine Learning and Computational Intelligence College of Mathematics and Information Science Hebei University Baoding071002 China Beijing Institute for Scientific and Engineering Computing Beijing University of Technology Beijing100124 China

Unsupervised cross-modal hashing has achieved great success in various information retrieval applications owing to its efficient storage usage and fast retrieval speed. Recent studies have primarily focused on training the hash-encoded networks by calculating a sample-based similarity matrix to improve the retrieval performance. However, there are two issues remain to solve: (1) The current sample-based similarity matrix only considers the similarity between image-text pairs, ignoring the different information densities of each modality, which may introduce additional noise and fail to mine key information for retrieval;(2) Most existing unsupervised cross-modal hashing methods only consider alignment between different modalities, while ignoring consistency between each modality, resulting in semantic conflicts. To tackle these challenges, a novel Deep High-level Concept-mining Jointing Hashing (DHCJH) model for unsupervised cross-modal retrieval is proposed in this study. DHCJH is able to capture the essential high-level semantic information from image modalities and integrate into the text modalities to improve the accuracy of guidance information. Additionally, a new hashing loss with a regularization term is introduced to avoid the cross-modal semantic collision and false positive pairs problems. To validate the proposed method, extensive comparison experiments on benchmark datasets are conducted. Experimental findings reveal that DHCJH achieves superior performance in both accuracy and efficiency. The code of DHCJH is available at Github. © 2024 The Author(s)

关键词： Online searching

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hp-VERSION C1-CONTINUOUS PETROV-GALERKIN METHOD FOR NONLINEAR SECOND-ORDER INITIAL VALUE PROBLEMS WITH APPLICATION TO WAVE EQUATIONS

arXiv

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arXiv 2023年

作者： Wang, Lina Zhang, Mingzhu Tian, Hongjiong Yi, Lijun Department of Mathematics Shanghai Normal University Shanghai200234 China School of Science Henan University of Engineering Zhengzhou451191 China Scientific Computing Key Laboratory of Shanghai Universities Shanghai200234 China

We introduce and analyze an hp-version C1-continuous Petrov-Galerkin (CPG) method for nonlinear initial value problems of second-order ordinary differential equations. We derive apriori error estimates in the L2-, L∞-, H1- and H2-norms that are completely explicit in the local time steps and local approximation degrees. Moreover, we show that the hp-version C1-CPG method superconverges at the nodal points of the time partition with regard to the time steps and approximation degrees. As an application, we apply the hp-version C1-CPG method to time discretization of nonlinear wave equations. Several numerical examples are presented to verify the theoretical *** Codes 65L60, 65L05, 65L70 Copyright © 2023, The Authors. All rights reserved.

关键词： Wave equations

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Random ISAC Signals Deserve Dedicated Precoding

arXiv

引用

arXiv 2023年

作者： Lu, Shihang Liu, Fan Dong, Fuwang Xiong, Yifeng Xu, Jie Liu, Ya-Feng Jin, Shi Southern University of Science and Technology Shenzhen518055 China The School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China Shenzhen518172 China The State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China National Mobile Communications Research Laboratory Southeast University Nanjing210096 China

Radar systems typically employ well-designed deterministic signals for target sensing, while integrated sensing and communications (ISAC) systems have to adopt random signals to convey useful information. This paper analyzes the sensing and ISAC performance relying on random signaling in a multi-antenna system. Towards this end, we define a new sensing performance metric, namely, ergodic linear minimum mean square error (ELMMSE), which characterizes the estimation error averaged over random ISAC signals. Then, we investigate a data-dependent precoding (DDP) scheme to minimize the ELMMSE in sensing-only scenarios, which attains the optimized performance at the cost of high implementation overhead. To reduce the cost, we present an alternative data-independent precoding (DIP) scheme by stochastic gradient projection (SGP). Moreover, we shed light on the optimal structures of both sensing-only DDP and DIP precoders. As a further step, we extend the proposed DDP and DIP approaches to ISAC scenarios, which are solved via a tailored penalty-based alternating optimization algorithm. Our numerical results demonstrate that the proposed DDP and DIP methods achieve substantial performance gains over conventional ISAC signaling schemes that treat the signal sample covariance matrix as deterministic, which proves that random ISAC signals deserve dedicated precoding designs. © 2023, CC BY.

关键词： Numerical methods

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Clustering-based Low Rank Approximation Method

arXiv

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arXiv 2025年

作者： Zhu, Yujun Zhu, Jie Arshad, Hizba Wang, Zhongming Ming, Ju School of Mathematics and Statistics Huazhong University of Science and Technology Wuhan China Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and Technology Wuhan China Department of Mathematics and Statistics Florida International University MiamiFL United States

We propose a clustering-based generalized low rank approximation method, which takes advantage of appealing features from both the generalized low rank approximation of matrices (GLRAM) and cluster analysis. It exploits a more general form of clustering generators and similarity metrics so that it is more suitable for matrix-structured data relative to conventional partitioning methods. In our approach, we first pre-classify the initial matrix collection into several small subset clusters and then sequentially compress the matrices within the clusters. This strategy enhances the numerical precision of the low-rank approximation. In essence, we combine the ideas of GLRAM and clustering into a hybrid algorithm for dimensionality reduction. The proposed algorithm can be viewed as the generalization of both techniques. Theoretical analysis and numerical experiments are established to validate the feasibility and effectiveness of the proposed algorithm. © 2025, CC BY-NC-ND.

关键词： Matrix algebra

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A diffuse-interface lattice Boltzmann method for the dissolution through nonlinear heterogeneous reaction

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Physics of Fluids 2025年第5期37卷

作者： Yang, Xiaofeng Zhan, Chengjie Liu, Xi Chai, Zhenhua School of Mathematics and Statistics Huazhong University of Science and Technology Wuhan430074 China Institute of Interdisciplinary Research for Mathematics and Applied Science Huazhong University of Science and Technology Wuhan430074 China Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and Technology Wuhan430074 China The State Key Laboratory of Intelligent Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan430074 China

In this work, a diffuse-interface lattice Boltzmann method (DI-LBM) is proposed for the dissolution through nonlinear heterogeneous reaction. In this method, the sharp boundary between the fluid and solid phases is replaced by a diffuse interface with a nonzero thickness. To describe the changes of physical variables from the fluid region to the solid region, a smooth function is introduced, and simultaneously, the nonlinear Robin boundary condition imposed on the fluid-solid interface is reformulated as a source term into the modified convection-diffusion equation. We then test the DI-LBM through several benchmark problems, and find that the numerical results are in agreement with the analytical solutions and available data. Finally, the present DI-LBM is adopted to study the dissolution in a two-dimensional porous medium, and the results show that with the decrease in reaction order, the reactant in the central region with a large fluid velocity reacts faster and forms a conical pathway. © 2025 Author(s).

关键词： Kinetic theory of gases

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ON THE KELLER-SEGEL MODELS INTERACTING WITH A STOCHASTICALLY FORCED INCOMPRESSIBLE VISCOUS FLOW IN R2

arXiv

引用

arXiv 2022年

作者： Zhang, Lei Liu, Bin School of Mathematics and Statistics Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and Technology Hubei Wuhan430074 China

This paper considers the Keller-Segel model coupled to stochastic Navier-Stokes equations (KS-SNS, for short), which describes the dynamics of oxygen and bacteria densities evolving within a stochastically forced 2D incompressible viscous flow. Our main goal is to investigate the existence and uniqueness of global solutions (strong in the probabilistic sense and weak in the PDE sense) to the KS-SNS system. A novel approximate KS-SNS system with proper regularization and cut-off operators in Hs(R2) is introduced, and the existence of approximate solution is proved by some a priori uniform bounds and a careful analysis on the approximation scheme. Under appropriate assumptions, two types of stochastic entropy-energy inequalities that seem to be new in their forms are derived, which together with the Prohorov theorem and Jakubowski-Skorokhod theorem enables us to show that the sequence of approximate solutions converges to a global martingale weak solution. In addition, when χ(·) ≡ const. > 0, we prove that the solution is pathwise unique, and hence by the Yamada-Wantanabe theorem that the KS-SNS system admits a unique global pathwise weak solution. Copyright © 2022, The Authors. All rights reserved.

关键词： Navier Stokes equations

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The Convergence Properties of Infeasible Inexact Proximal Alternating Linearized Minimization

arXiv

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arXiv 2022年

作者： Hu, Yukuan Liu, Xin State Key Laboratory of Scientific and Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences University of Chinese Academy of Sciences China

The proximal alternating linearized minimization method (PALM) suits well for solving blockstructured optimization problems, which are ubiquitous in real applications. In the cases where subproblems do not have closed-form solutions, e.g., due to complex constraints, infeasible subsolvers are indispensable, giving rise to an infeasible inexact PALM (PALM-I). Numerous efforts have been devoted to analyzing feasible PALM, while little attention has been paid to PALM-I. The usage of PALM-I thus lacks theoretical guarantee. The essential difficulty of analyses consists in the objective value nonmonotonicity induced by the infeasibility. We study in the present work the convergence properties of PALM-I. In particular, we construct a surrogate sequence to surmount the nonmonotonicity issue and devise an implementable inexact criterion. Based upon these, we manage to establish the stationarity of any accumulation point and, moreover, show the iterate convergence and the asymptotic convergence rates under the assumption of the Lojasiewicz property. The prominent advantages of PALM-I on CPU time are illustrated via numerical experiments on problems arising from quantum physics and 3D anisotropic frictional *** Codes 49M27, 65K05, 90C26, 90C30 © 2022, CC BY.

关键词： Linearization

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A Variance-Reduced Stochastic Gradient Tracking Algorithm for Decentralized Optimization with Orthogonality Constraints

arXiv

引用

arXiv 2022年

作者： Wang, Lei Liu, Xin State Key Laboratory of Scientific and Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences University of Chinese Academy of Sciences China

Decentralized optimization with orthogonality constraints is found widely in scientific computing and data science. Since the orthogonality constraints are nonconvex, it is quite challenging to design efficient algorithms. Existing approaches leverage the geometric tools from Riemannian optimization to solve this problem at the cost of high sample and communication complexities. To relieve this difficulty, based on two novel techniques that can waive the orthogonality constraints, we propose a variance-reduced stochastic gradient tracking (VRSGT) algorithm with the convergence rate of O(1/k) to a stationary point. To the best of our knowledge, VRSGT is the first algorithm for decentralized optimization with orthogonality constraints that reduces both sampling and communication complexities simultaneously. In the numerical experiments, VRSGT has a promising performance in a real-world autonomous driving application. Copyright © 2022, The Authors. All rights reserved.

关键词： Stochastic systems

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Parallel Numerical Simulation of Blood Flows in Patient-specific Aortic Dissection 6

Parallel Numerical Simulation of Blood Flows in Patient-spec...

引用

6th IEEE International Conference on Computer and Communication Systems, ICCCS 2021

作者： Tu, Jiali Qin, Shanlin Chen, Rongliang Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China University of Chinese Academy of Sciences Beijing China Shenzhen Key Laboratory for Exascale Engineering and Scientific Computing Shenzhen China

ISBN: (纸本)9780738126043

Aortic dissection is the separation of the inner layers of the aortic wall, which allows the blood to flow into it. The computational fluid dynamics allows a better understanding of its pathology and treatment. However, it is time-consuming due to the computationally expensive. In this work, we introduce a parallel algorithm for accurate and fast three-dimensional blood flow simulation of a patient-specific full-size aorta with dissections. Specifically, the unsteady Navier-Stokes equations are discretized by a unstructured finite element method in space and a fully implicit finite difference method in time, and the fully coupled nonlinear system at each time step is solved by a domain decomposition method based parallel scalable iterative algorithm. The numerical results are carefully analyzed and it shows that the simulated pressure, velocity, and wall shear stress are within a reasonable range. In addition, the algorithm achieves a parallel efficiency of 40% when using 3840 processor cores on the Tianhe-2A supercomputer, which shows the potential to do fast and high fidelity blood flow simulations of aortic dissection. © 2021 IEEE.

关键词： Iterative methods

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GLOBAL MARTINGALE WEAK SOLUTIONS FOR THE THREE-DIMENSIONAL STOCHASTIC CHEMOTAXIS-NAVIER-STOKES SYSTEM WITH LÉVY PROCESSES

arXiv

引用

arXiv 2022年

This paper considers the three-dimensional stochastic chemotaxis-Navier-Stokes (SCNS) system subjected to a Lévy-type random external force in a bounded domain. Until recently, the existed results concerning global solvability of SCNS system mainly concentrated on the case of two spatial dimensions, little is known about the SCNS system in dimension three. We prove in the present work that the initial-boundary value problem for the three-dimensional SCNS system has at least one global martingale solution under proper assumptions, which is weak in both the analytical and stochastic sense. A new stochastic analogue of entropy-energy inequality and an uniform boundedness estimate are derived, which enable us to construct global-in-time approximate solutions from a suitably regularized SCNS system via the Contraction Mapping Principle. The proof of the existence of martingale solution is based on a stochastic compactness method and an elaborate identification of the limits procedure, where the Jakubowski-Skorokhod Theorem is applied to deal with the phase spaces equipped with weak topology. Copyright © 2022, The Authors. All rights reserved.

关键词： Stochastic systems

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