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Methods for solving equations with errors based on the HHL algorithm

The Journal of China Universities of Posts and Telecommunications 2022年第4期29卷 9-20页

作者： LüLihui Wang Hong Ma Zhi Duan Qianheng Fei Yangyang Meng Xiangdong State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou 450001China Henan Key Laboratory of Network Cryptography Technology Zhengzhou 450001China

To solve polynomial systems,Harrow,Hassidim,and Lloyd(HHL)proposed a quantum algorithm called HHL *** on the HHL algorithm,Chen et *** an algorithm,the solving the Boolean solutions of polynomial systems(PoSSoB)***,Ding et *** the Boolean Macaulay matrix and analyzed the lower bound on the condition *** by Ding et al.’s research,several related algorithms are proposed in this ***,the improved PoSSoB algorithm using the Boolean Macaulay matrix is proved to have lower ***,for solving equations with errors,a quantum algorithm for the max-polynomial system solving(Max-PoSSo)problem is proposed based on the improved PoSSoB ***,the Max-PoSSo algorithm is extended to the learning with errors(LWE)problem and its special case,the learning parity with noise(LPN)problem,providing a quantitative criterion,the condition number,for the security of these basic problems.

关键词： Harrow Hassidim and Lloyd polynomial system solving max-polynomial system solving learning parity with noise learning with errors

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MAST-Pro: Dynamic Mixture-of-Experts for Adaptive Segmentation of Pan-Tumors with Knowledge-Driven Prompts

arXiv

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arXiv 2025年

作者： Meng, Runqi Song, Sifan Jin, Pengfei Oh, Yujin Teng, Lin Wang, Yulin Sun, Yiqun Chen, Ling Li, Xiang Li, Quanzheng Guo, Ning Shen, Dinggang School of Biomedical Engineering State Key Laboratory of Advanced Medical Materials and Devices ShanghaiTech University China Center of Advanced Medical Computing and Analysis Massachusetts General Hospital Harvard Medical School Harvard University United States Shanghai United Imaging Intelligence Co. Ltd China Shanghai Clinical Research and Trial Center China

Accurate tumor segmentation is crucial for cancer diagnosis and treatment. While foundation models have advanced general-purpose segmentation, existing methods still struggle with: (1) limited incorporation of medical priors, (2) imbalance between generic and tumor-specific features, and (3) high computational costs for clinical adaptation. To address these challenges, we propose MAST-Pro (Mixture-of-experts for Adaptive Segmentation of pan-Tumors with knowledge-driven Prompts), a novel framework that integrates dynamic Mixture-of-Experts (D-MoE) and knowledge-driven prompts for pan-tumor segmentation. Specifically, text and anatomical prompts provide domain-specific priors, guiding tumor representation learning, while D-MoE dynamically selects experts to balance generic and tumor-specific feature learning, improving segmentation accuracy across diverse tumor types. To enhance efficiency, we employ Parameter-Efficient Fine-Tuning (PEFT), optimizing MAST-Pro with significantly reduced computational overhead. Experiments on multi-anatomical tumor datasets demonstrate that MAST-Pro outperforms state-of-the-art approaches, achieving up to a 5.20% improvement in average DSC while reducing trainable parameters by 91.04%, without compromising accuracy. © 2025, CC BY-NC-ND.

关键词： Image segmentation

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Complexity of Tensor Product Functions in Representing Antisymmetry

arXiv

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arXiv 2025年

作者： Wang, Yuyang Hu, Yukuan Liu, Xin State Key Laboratory of Scientific and Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing100049 China CERMICS Ecole des Ponts IP Paris Marne-la-Vallée77455 France

Tensor product function (TPF) approximations have been widely adopted in solving high-dimensional problems, such as partial differential equations and eigenvalue problems, achieving desirable accuracy with computational overhead that scales linearly with problem dimensions. However, recent studies have underscored the extraordinarily high computational cost of TPFs on quantum many-body problems, even for systems with as few as three particles. A key distinction in these problems is the antisymmetry requirement on the unknown functions. In the present work, we rigorously establish that the minimum number of involved terms for a class of TPFs to be exactly antisymmetric increases exponentially fast with the problem dimension. This class encompasses both traditionally discretized TPFs and the recent ones parameterized by neural networks. Our proof exploits the link between the antisymmetric TPFs in this class and the corresponding antisymmetric tensors and focuses on the Canonical Polyadic rank of the latter. As a result, our findings uncover a fundamental incompatibility between antisymmetry and low-rank TPFs in high-dimensional contexts and offer new insights for further developments. Copyright © 2025, The Authors. All rights reserved.

关键词： Tensors

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A Large-Scale Study of Failures on Petascale Supercomputers

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Journal of Computer Science & Technology 2018年第1期33卷 24-41页

作者： Rui-Tao Liu Zuo-Ning Chen State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi 213215 China National Research Center of Parallel Computer Engineering and Technology Beijing 100190 China

With the rapid development of supercomputers, the scale and complexity are ever increasing, and the reliability and resilience are faced with larger challenges. There are many important technologies in fault tolerance, such as proacrive failure avoidance technologies based on fault prediction, reactive fault tolerance based on checkpoint, and scheduling technologies to improve reliability. Both qualitative and quantitative descriptions on characteristics of system faults are very critical for these technologies, This study analyzes the source of failures on two typical petascale supercomputers called Sunway BlueLight （based on multi-core CPUs） and Sunway TaihuLight （based on heterogeneous manycore CPUs）. It uncovers some interesting fault characteristics and finds unknown correlation relationship among main components＇ faults. Finally the paper analyzes the failure time of the two supercomputers in various grains of resource and different time spans, and builds a uniform multi-dimensional failure time model for petascale supereomputers.

关键词： petascale supercomputer fault characteristic correlation relationship multi-dimension failure time model

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A TrustEnclave-Based Architecture for Ensuring Run-Time Security in Embedded Terminals

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Tsinghua Science and Technology 2017年第5期22卷 447-457页

作者： Rui Chang Liehui Jiang Wenzhi Chen Yaobin Xie Zhongyong Lu the State Key Laboratory of Mathematic Engineering and Advanced Computing the Department of Computer Zhejiang University

The run-time security guarantee is a hotspot in current cyberspace security research, especially on embedded terminals, such as smart hardware as well as wearable and mobile devices. Typically, these devices use universal hardware and software to connect with public networks via the Internet, and are probably open to security threats from Trojan viruses and other malware. As a result, the security of sensitive personal data is threatened and economic interests in the industry are compromised. To address the run-time security problems efficiently, first, a TrustEnclave-based secure architecture is proposed, and the trusted execution environment is constructed by hardware isolation technology. Then the prototype system is implemented on real TrustZone-enabled hardware devices. Finally, both analytical and experimental evaluations are provided. The experimental results demonstrate the effectiveness and feasibility of the proposed security scheme.

关键词： run-time security trusted execution environment hardware isolation TrustZone

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Integrating Neighborhood Geographic Distribution and Social Structure Influence for Social Media User Geolocation

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Computer Modeling in engineering & Sciences 2024年第9期140卷 2513-2532页

作者： Meng Zhang Xiangyang Luo Ningbo Huang Key Laboratory of Cyberspace Situation Awareness of Henan Province Zhengzhou450001China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001China

Geolocating social media users aims to discover the real geographical locations of users from their publicly available data,which can support online location-based applications such as disaster alerts and local content *** relationship-based methods represent a classical approach for geolocating social ***,geographically proximate relationships are sparse and challenging to discern within social networks,thereby affecting the accuracy of user *** address this challenge,we propose user geolocation methods that integrate neighborhood geographical distribution and social structure influence(NGSI)to improve geolocation ***,we propose a method for evaluating the homophily of locations based on the k-order neighbor-hood geographic distribution(k-NGD)similarity among *** are notable differences in the distribution of k-NGD similarity between location-proximate and non-location-proximate *** this distinction,we filter out non-location-proximate social relationships to enhance location homophily in the social *** better utilize the location-proximate relationships in social networks,we propose a graph neural network algorithm based on the social structure *** algorithm enables us to perform a weighted aggregation of the information of users’multi-hop neighborhood,thereby mitigating the over-smoothing problem of user features and improving user geolocation *** results on real social media dataset demonstrate that the neighborhood geographical distribution similarity metric can effectively filter out non-location-proximate social ***,compared with 7 existing social relationship-based user positioning methods,our proposed method can achieve multi-granularity user geolocation and improve the accuracy by 4.84%to 13.28%.

关键词： User geolocation social media neighborhood geographic distribution structure influence

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Searching for similar binary code based on the influence of basic block vertex 3

Searching for similar binary code based on the influence of ...

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2021年第三届先进计算机技术、信息科学与通信国际会议(CTISC2021)

作者： Xiaodong Zhu Liehui Jiang Zeng Chen Lin Yan State key laboratory of mathematical engineering and advanced computing

ISBN: (纸本)9781665418683

Binary code similarity detection(BCSD) has many security applications and has attracted a lot of focus. But existing solutions for BCSD problems mainly focus on comparing the similarity between two binary functions and what need to be compared is not always a pair of equal-size binary *** solve the problem of searching similar binary code for a small size program in a large size program, in this manuscript,we propose a searching method based on the influence of basic block vertex. Firstly, we formalize the similar code searching problem as a subgraph matching problem and extract the attributed control flow graphs(ACFGs) of the binary ***, we propose a novel metrics to measure the influence of each basic block vertex in query ACFGs and choose the vertex with the largest influence value as the central node. Next, we take the matching nodes of the central node in target ACFG as seed nodes and extending each candidate sub-area from the seed nodes. At last, these candidate sub-areas are further filtered and similar subgraphs are verified in these *** results indicate that the proposed method can find similar binary code efficiently.

关键词： Measurement Matched filters Information science Binary codes Search problems Security Flow graphs

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Optimal Bilinear Equalizer for Cell-Free Massive MIMO Systems over Correlated Rician Channels

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IEEE Transactions on Signal Processing 2025年

作者： Wang, Zhe Zhang, Jiayi Bjornson, Emil Niyato, Dusit Ai, Bo Beijing Jiaotong University State Key Laboratory of Advanced Rail Autonomous Operation Beijing100044 China Beijing Jiaotong University School of Electronics and Information Engineering Beijing100044 China KTH Royal Institute of Technology Department of Computer Science Stockholm114 28 Sweden Nanyang Technological University College of Computing & Data Science 639798 Singapore

In this paper, we explore the low-complexity optimal bilinear equalizer (OBE) combining scheme design for cell-free massive multiple-input multiple-output networks with spatially correlated Rician fading *** provide a spectral efficiency (SE) performance analysis framework for both the centralized and distributed processing schemes with bilinear equalizer (BE)-structure combining schemes applied. The BE-structured combining is a set of schemes that are constructed by the multiplications of channel statistics-based BE matrices and instantaneous channel estimates. Notably, we derive closed-form achievable SE expressions for centralized and distributed BE-structured combining schemes. We propose one centralized and two distributed OBE schemes: Centralized OBE (C-OBE), Distributed OBE based on Global channel statistics (DG-OBE), and Distributed OBE based on Local channel statistics (DL-OBE), which maximize their respective SE expressions. OBE matrices in these schemes are tailored based on varying levels of channel statistics. Notably, we obtain new and insightful closed-form results for the C-OBE, DG-OBE, and DL-OBE combining schemes. Numerical results demonstrate that the proposed OBE schemes can achieve excellent SE, even in scenarios with severe pilot contamination. © 2025 IEEE. All rights reserved.

关键词： Fading channels

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Research on Stream Cipher Model Based on Chaos Theory

Research on Stream Cipher Model Based on Chaos Theory

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第四届智能结构与振动控制国际会议

作者： Sun Wenjie State Key Laboratory of Mathematical Engineering and Advanced Computing

ISBN: (纸本)9783038350507

Chaos is a similar and random process which is very sensitive to initial value in deterministic *** is a performance of nonlinear dynamical system with built-in *** with the advantages and disadvantages of the present chaos encryption model,the paper proposes a chaotic stream cipher model based on chaos theory,which not only overcomes finite precision effect,but also improves the randomness of chaotic system and output *** Sequence cycle theory generated by the algorithm can reach more than 10600 at least,which completely satisfies the actual application requirements of stream cipher system.

关键词： Chaos Theory,Stream Cipher,Algorithm

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Information diffusion network inferring and pathway tracking

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Science China(Information Sciences) 2015年第9期58卷 135-149页

作者： ZHOU DongHao HAN WenBao WANG YongJun YUAN BaoDi College of Computer National University of Defense Technology State Key Laboratory of Mathematical Engineering and Advanced Computing College of Computer Science and Technology Fudan University

Network diffusion, such as spread of ideas, rumors, contagious disease, or a new type of behaviors, is one of the fundamental processes within networks. Designing effective strategies for influence spread maximization, rumor spread minimization, or epidemic immunization has attracted considerable research attention. However, a key challenge is that many times we can only observe the trace of contagion spreading across network, but the underlying network structure is unknown and the transmission rates between node pairs are unclear to us. In this paper, given the observed information cascades, we aim to address two problems:diffusion network structure inferring and information diffusion pathways tracking. We propose a novel probabilistic model called Network Inferring from Multidimensional Features of Cascades(NIMFC) which takes into account heterogeneous features, including temporal and topological features of cascades, node attributes, and information content, to infer the latent network structure and transmission rates of edges. Also, based on the inferred network structure, we may track diffusion pathways of a cascade in social networks. We use blocked coordinate descent method to learn a sparse estimation of the latent network. Our proposed model NIMFC is evaluated both on large synthetic and real-world data sets, and experimental results show that our method significantly outperforms state-of-the-art models both in terms of recovering the latent network structure and information pathway tracking.

关键词： diffusion network network inferring information pathway tracking temporal feature node attributes topological feature informatio

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