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SSRN 2024年

作者： Li, Xuetong Zhang, Xiao-Dong Funded Key Lab of Scientific and Engineering Computing Shanghai Center for Applied Mathematics Shanghai Jiao Tong University Shanghai200240 China

Multisource data has encouraged the development of advanced clustering algorithms, such as multi-view clustering, which critically relies on constructing similarity matrices. Traditional algorithms typically generate these matrices from node attributes alone. However, real-world networks often include pairwise directed topological structures critical for clustering. This paper introduces a novel multi-view clustering algorithm, AAS. It proposes a two-step proximity approach via anchors in each view, integrating attribute and directed structural information. This approach enhances the clarity of class features in the similarity matrices. The construction of the anchor structural similarity matrix leverages strongly connected components of directed graphs. The entire process—from similarity matrices construction to clustering—is consolidated into a unified optimization framework. Comparative experiments on the modified Attribute SBM dataset against eight algorithms affirm the effectiveness and superiority of AAS. © 2024, The Authors. All rights reserved.

关键词： Data fusion

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Multi-View Clustering Integrating Anchor Attribute and Structural Information

SSRN

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SSRN 2024年

作者： Li, Xuetong Zhang, Xiao-Dong Funded Key Lab of Scientific and Engineering Computing Shanghai Center for Applied Mathematics Shanghai Jiao Tong University Shanghai200240 China

Constructing the similarity matrix is a pivotal step in multi-view clustering, serving as the foundation for subsequent clustering processes. Most multi-view clustering algorithms focus on computing similarity matrices based solely on attribute information, often overlooking the significance of inter-node interaction structures. This paper introduces a novel multi-view clustering algorithm, abbreviated as AAS. This algorithm not only integrates information across multiple views but also combines the attribute information of nodes with their structural interactions, thereby enabling the similarity matrix to more accurately reflect actual classifications. Furthermore, the complexity of the algorithm is simplified through the utilization of anchor method, and a more flexible and representative method for selecting anchors is proposed. Ultimately, the process of solving the similarity matrix and clustering is integrated into a unified optimization framework. Experiments conducted on datasets generated by the improved Attribute SBM method, and comparative analyses with eight other algorithms, demonstrate the effectiveness and superiority of the proposed method. © 2024, The Authors. All rights reserved.

关键词： Clustering algorithms

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Toward the Impossibility of Perfect Complete Quantum PKE from OWFs 16

Toward the Impossibility of Perfect Complete Quantum PKE fro...

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16th Innovations in Theoretical Computer Science Conference, ITCS 2025

作者： Li, Longcheng Li, Qian Li, Xingjian Liu, Qipeng State Key Lab of Processors Institute of Computing Technology Chinese Academy of Sciences Beijing China Shenzhen International Center for Industrial and Applied Mathematics Shenzhen Research Institute of Big Data China Tsinghua University Beijing China University of California La Jolla San DiegoCA United States

ISBN: (纸本)9783959773614

In this paper, we study the impossibility of constructing perfect complete quantum public key encryption (QPKE) from quantumly secure one-way functions (OWFs) in a black-box manner. We show that this problem is connected to a fundamental conjecture about the roots of low-degree polynomials on the Boolean hypercube. Informally, the conjecture asserts that for every nonconstant low-degree polynomial, there exists a universal (randomized) way to modify a small number of input bits such that, for every input string, the polynomial evaluated on the modified input string avoids 0 with sufficiently large probability (over the choice of how the input string is modified). Assuming this conjecture, we demonstrate the impossibility of constructing QPKE from quantumly secure one-way functions in a black-box manner, by employing the information-theoretical approach recently developed by Li, Li, Li, and Liu (CRYPTO’24). Towards resolving this conjecture, we provide various pieces of evidence supporting it and prove some special cases. In particular, we fully rule out perfect QPKE from OWFs when the key generation algorithm only makes a logarithmic number of quantum queries, improving the previous work, which can only handle classical queries. © Longcheng Li, Qian Li, Xingjian Li, and Qipeng Liu.

关键词： Boolean functions

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Multi-view clustering integrating anchor attribute and structural information

arXiv

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arXiv 2024年

作者： Li, Xuetong Zhang, Xiao-Dong Funded Key Lab of Scientific and Engineering Computing Shanghai Center for Applied Mathematics Shanghai Jiao Tong University Shanghai200240 China

Multisource data has driven the development of advanced clustering algorithms, such as multi-view clustering, which critically rely on the construction of similarity matrices. Traditional algorithms typically generate these matrices based solely on node attributes. However, for certain directed real-world networks, neglecting the asymmetric structural relationships between nodes may compromise the accuracy of clustering results. This paper introduces a novel multiview clustering algorithm, AAS, which employs a two-step proximity approach using anchors in each view, effectively integrating both attribute and directed structural information. This method enhances the clarity of cluster features within the similarity matrices. The construction of the anchor structural similarity matrix utilizes strongly connected components of directed graphs. The entire process—from the construction of similarity matrices to clustering—is formulated within a unified optimization framework. Comparative experiments conducted on the modified Attribute SBM dataset, benchmarked against seven other algorithms, demonstrate the effectiveness and superiority of AAS. Copyright © 2024, The Authors. All rights reserved.

关键词： Data fusion

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An explicit, energy-conserving particle-in-cell scheme

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Journal of Computational Physics 2025年 537卷

作者： Ricketson, Lee F. Hu, Jingwei Lawrence Livermore National Laboratory Center for Applied Scientific Computing 7000 East Avenue LivermoreCA94550 United States Department of Applied Mathematics University of Washington Box 353925 SeattleWA98195 United States

We present an explicit temporal discretization of particle-in-cell schemes for the non-relativistic Vlasov equation that results in exact energy conservation when combined with an appropriate spatial discretization. The scheme is inspired by a simple, second-order explicit scheme that conserves energy exactly in the Eulerian context. We show that direct translation to particle-in-cell does not result in strict conservation, but derive a simple correction based on an analytically solvable optimization problem that recovers conservation. While this optimization problem is not guaranteed to have a real solution for every particle, we provide a correction that makes imaginary values extremely rare and still admits O(10−12) fractional errors in energy for practical simulation parameters. We present the scheme in both electrostatic – where we use the Ampère formulation – and electromagnetic contexts. With an electromagnetic field solve, the field update is most naturally linearly implicit, but the more computationally intensive particle update remains fully explicit. We also show how the scheme can be extended to use the fully explicit leapfrog and pseudospectral analytic time-domain (PSATD) field solvers. The scheme is tested on standard kinetic plasma problems, confirming its conservation properties. © 2025 Elsevier Inc.

关键词： Energy efficiency

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Harnessing computational models to uncover the role of the immune system in tuberculosis treatment

Harnessing computational models to uncover the role of the i...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Mastrostefano, Enrico Ravoni, Alessandro Onofri, Elia Tieri, Paolo Castiglione, Filippo National Research Council Institute for Applied Computing 'Mauro Picone' Rome Italy University of Roma Tre Dept. Mathematics and Physics Rome Italy Technology Innovation Institute Biotechnology Research Center Abu Dhabi United Arab Emirates

ISBN: (纸本)9798350337488

The importance of the immune system (IS) in tuberculosis (TB) drug development is often underestimated because of the intricate nature of experiments and the specialized knowledge needed. In vitro and animal studies fall short in replicating the intricate reactions of the human IS to drugs and infections. In this study, we present our initial efforts in employing an in silico approach to comprehend how an individual's IS impacts the efficacy of therapy, particularly in managing mycobacterium tuberculosis (Mtb) infection and minimizing the risk of relapse. We employed a well-established agent-based IS simulator called C-IMMSIM. We conducted simulations to investigate the long-term outcomes of TB disease in a virtual cohort infected with Mtb over a 50-year period. Our simulations revealed that individuals with competent IS showed a high success rate in containing Mtb infection. Furthermore, to better understand the dynamic interactions between Mtb and the IS, we deliberately introduced specific IS deficiencies, thus successfully inducing short-term relapses and mortality. These results confirm the model's ability to elucidate the mechanisms underlying the interactions between Mtb and the IS. © 2023 IEEE.

关键词： C-IMMSIM epidemiological distribution in-silico modelling Mycobacterium tuberculosis pathogen-drug interaction

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Smoothers with localized residual computations for geometric multigrid methods

arXiv

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arXiv 2024年

作者： Wichrowski, Michal Munch, Peter Kronbichler, Martin Kanschat, Guido Interdisciplinary Center for Scientifc Computing Heidelberg University Heidelberg Germany High-Performance Scientific Computing University of Augsburg Germany Applied Numerics Faculty of Mathematics Ruhr University Bochum Germany

We improve the performance of multigrid solvers on many-core architectures with cache hierarchies by reorganizing operations in the smoothing step to minimize memory transfers. We focus on patch smoothers, which offer robust convergence rates with respect to the finite element degree for various equations, in the setting of multiplicative subspace correction for numerical efficiency. By combining the computation of local residuals with local solvers, we increase the locality of the problem and thus reduce data transfers. The thread-parallel implementation of this algorithm is based on coloring, which contradicts cache efficiency. We improve data locality by rearranging the loop into batches so that more data can be reused. The organization of consecutive batches prioritizes data locality. © 2024, CC BY-NC-ND.

关键词： Finite element method

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Efficient Implementation of Liquid Crystal Simulation Software on Modern HPC Platforms

Supercomputing Frontiers and Innovations

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Supercomputing Frontiers and Innovations 2021年第3期8卷 104-125页

作者： Afanasyev, Ilya V. Lichmanov, Dmitry I. Rudyak, Vladimir Yu. Voevodin, Vadim V. Moscow Center of Fundamental and Applied Mathematics Moscow Russia Research Computing Center Lomonosov Moscow State University Moscow Russia Faculty of Physics Lomonosov Moscow State University Moscow Russia

In this paper we demonstrate the process of efficient porting a software package for Markov chain Monte Carlo (MCMC) simulations on a finite cubic lattice on multiple modern architectures: Pascal, Volta and Turing NVIDIA GPUs, NEC SX-Aurora TSUBASA vector engines and Intel Xeon Gold processors. In the studied software, MCMC methodology is used for simulations of liquid crystal structures, but it can be as well employed in a wide range of problems of mathematical physics and numerical methods. The main goals of this work are to determine the best software optimization strategy for this class of algorithms and to examine the speed and the efficiency of such simulations on modern HPC platforms. We evaluate the effects of various optimizations, such as using more suitable memory access patterns, multitasking for efficient utilization of massive parallelism on the target architectures, improved cache hit-rates, parallel workload balancing, etc. We perform a detailed performance analysis for each target platform using software tools such as nvprof, Ftrace and VTune. On this basis, we evaluate and compare the efficiency of the developed computational kernels on different platforms and subsequently rank these platforms by their performance. The results show that NVIDIA GPU and NEC SX-Aurora TSUBASA platforms, although at first glance seem very different, require similar optimization approaches in many cases due to similarities in data processing principles. © 2021 The Authors. This paper is published with open access at ***. All Rights Reserved.

关键词： Liquid crystals

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Bayesian optimization of function networks with partial evaluations 24

Bayesian optimization of function networks with partial eval...

引用

Proceedings of the 41st International Conference on Machine Learning

作者： Poompol Buathong Jiayue Wan Raul Astudillo Samuel Daulton Maximilian Balandat Peter I. Frazier Center for Applied Mathematics Cornell University School of Operations Research and Information Engineering Cornell University Department of Computing and Mathematical Sciences Caltech Meta

Bayesian optimization is a powerful framework for optimizing functions that are expensive or time-consuming to evaluate. Recent work has considered Bayesian optimization of function networks (BOFN), where the objective function is given by a network of functions, each taking as input the output of previous nodes in the network as well as additional parameters. Leveraging this network structure has been shown to yield significant performance improvements. Existing BOFN algorithms for general-purpose networks evaluate the full network at each iteration. However, many real-world applications allow for evaluating nodes individually. To exploit this, we propose a novel knowledge gradient acquisition function that chooses which node and corresponding inputs to evaluate in a cost-aware manner, thereby reducing query costs by evaluating only on a part of the network at each step. We provide an efficient approach to optimizing our acquisition function and show that it outperforms existing BOFN methods and other benchmarks across several synthetic and real-world problems. Our acquisition function is the first to enable cost-aware optimization of a broad class of function networks.

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PARALLEL-IN-TIME SOLUTION OF HYPERBOLIC PDE SYSTEMS VIA CHARACTERISTIC-VARIABLE BLOCK PRECONDITIONING

arXiv

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arXiv 2024年

作者： De Sterck, H. Falgout, R.D. Krzysik, O.A. Schroder, J.B. Department of Applied Mathematics University of Waterloo WaterlooON Canada Center for Applied Scientific Computing Lawrence Livermore National Laboratory LivermoreCA United States Department of Mathematics and Statistics University of New Mexico AlbuquerqueNM United States

We consider the parallel-in-time solution of hyperbolic partial differential equation (PDE) systems in one spatial dimension, both linear and nonlinear. In the nonlinear setting, the discretized equations are solved with a preconditioned residual iteration based on a global linearization. The linear(ized) equation systems are approximately solved parallel-in-time using a block preconditioner applied in the characteristic variables of the underlying linear(ized) hyperbolic PDE. This change of variables is motivated by the observation that inter-variable coupling for characteristic variables is weak relative to intra-variable coupling, at least locally where spatio-temporal variations in the eigenvectors of the associated flux Jacobian are sufficiently small. For an -dimensional system of PDEs, applying the preconditioner consists of solving a sequence of scalar linear(ized)- advection-like problems, each being associated with a different characteristic wave-speed in the underlying linear(ized) PDE. We approximately solve these linear advection problems using multigrid reduction-in-time (MGRIT);however, any other suitable parallel-in-time method could be used. Numerical examples are shown for the (linear) acoustics equations in heterogeneous media, and for the (nonlinear) shallow water equations and Euler equations of gas dynamics with shocks and rarefactions. Copyright © 2024, The Authors. All rights reserved.

关键词： Advection

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