In machine learning, data privacy and security has become an increasingly growing concern. The introduction of machine unlearning offers the ability to address this issue through the removal of personal and sensitive ...
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An important research area for covered conductors is partial discharge detection. However, the complex distribution of high-frequency signals with particular noise and the long tail problem create a considerable obsta...
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The goal of community search is to provide effective solutions for real-time, high-quality community searches within large networks. In many practical applications, such as event organization and friend recommendation...
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ISBN:
(数字)9798350362480
ISBN:
(纸本)9798350362497
The goal of community search is to provide effective solutions for real-time, high-quality community searches within large networks. In many practical applications, such as event organization and friend recommendations, discovering various community structures within a network is crucial for users. However, existing community search algorithms rarely address issues within temporal graphs, and those that do often have two main limitations: (1) traditional community search methods become inefficient and experience significant increases in computation time when scaled to large graphs; (2) while GNN-based community search methods for temporal graphs offer generalizability, they often focus solely on community connectivity and lack cohesiveness. Therefore, we propose a new model PK-GCN, based on Graph Neural Networks (GNNs), to identify persistent k-core communities in temporal networks. This model can handle dynamic changes in temporal graphs and identify communities that persist over time. Compared to existing community search methods, our model not only finds communities with tighter structures but also allows for dynamic queries based on user input without needing retraining. Specifically, our model constructs features by integrating k-core information from core decomposition, graph features, and query features, resulting in more expressive node representations. Additionally, we designed a flexible dynamic query mechanism that allows users to input time information to query communities. Experiments on multiple datasets demonstrate that our model outperforms other GNN-based community search algorithms in F1-score.
At present, some performance evaluation methods of intelligent computing platform oriented to air combat decision algorithm have problems such as complex evaluation index system construction, poor evaluation accuracy,...
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Spatial transcriptomics data provides a unique opportunity to investigate both gene expression and spatial structure in tissues at the same time. However, incorporating spatial information to accurately identify spati...
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Compared to general quantum states, the sparse states arise more frequently in the field of quantum computation. In this work we consider the preparation for n-qubit sparse quantum states with s nonzero amplitudes and...
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Compared to general quantum states, the sparse states arise more frequently in the field of quantum computation. In this work we consider the preparation for n-qubit sparse quantum states with s nonzero amplitudes and propose two algorithms. The first algorithm uses O(ns/log2n+n) gates, improving upon previous methods by O(log2n). Moreover, the classical runtime of this algorithm is optimal. We further establish a matching lower bound for any algorithm that is not amplitude aware and employs at most poly(n) ancillary qubits. The second algorithm is tailored for binary strings that exhibit a short Hamiltonian path. An application is encoding the input data into a state with specified Hamming weight k in quantum machine learning, for which our algorithm constructs a circuit of size O(nklog2n). This surpasses previous results by O(k/log2n) and is close to the lower bound O(nk). The classical runtime is also nearly optimal. Both algorithms shrink the existing gap theoretically and provide increasing advantages numerically.
Complementary metal oxide semiconductor(CMOS)aging mechanisms including bias temperature instability(BTI)pose growing concerns about circuit *** results in threshold voltage increases on CMOS transistors,causing delay...
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Complementary metal oxide semiconductor(CMOS)aging mechanisms including bias temperature instability(BTI)pose growing concerns about circuit *** results in threshold voltage increases on CMOS transistors,causing delay shifts and timing violations on logic *** amount of degradation is dependent on the circuit workload,which increases the challenge for accurate BTI aging prediction at the design *** this paper,a BTI prediction method for logic circuits based on statistical static timing analysis(SSTA)is proposed,especially considering the correlation between circuit workload and BTI *** consists of a training phase,to discover the relationship between circuit scale and the required workload samples,and a prediction phase,to present the degradations under different workloads in Gaussian probability *** method can predict the distribution of degradations with negligible errors,and identify 50%more BTI-critical paths in an affordable time,compared with conventional methods.
In the near future of the noisy intermediate-scale quantum (NISQ) era, almost all quantum computing devices will be restricted to a specific fixed qubits connectivity architecture. Thus, the synthesis of quantum circu...
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In the near future of the noisy intermediate-scale quantum (NISQ) era, almost all quantum computing devices will be restricted to a specific fixed qubits connectivity architecture. Thus, the synthesis of quantum circuits with limited connectivity is urgent. We design quantum circuit synthesis algorithms for basic and essential synthesis problems, such as quantum state preparation, general unitary synthesis, and quantum isometries. For any architecture, the controlled not (cnot) count is at most 5/3 times the state-of-the-art result on complete-graph architecture. For some specific architectures, such as square-grid ones, the ratio is reduced to 1.126. The numerical simulation result is confirmatory of theoretical conclusions. Our algorithms significantly reduce by more than 50% additional cnot count compared to mapping algorithms. These algorithms help to implement the larger-scale algorithm in the physics device. Our results illustrate that well-designed synthesis algorithms can mitigate the problem of limited qubit connectivity in the NISQ era and may suggest the design of large-scale quantum devices.
Prototypical network based joint methods have attracted much attention in few-shot event detection, which carry out event detection in a unified sequence tagging framework. However, these methods suffer from the inacc...
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This paper presents three relatively effective numerical algorithms,i.e.,94 LVI algorithms of OIpU(one-iteration-perupdate) type,to handle time-dependent QP(quadratic programming) problems subject to two constraints r...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
This paper presents three relatively effective numerical algorithms,i.e.,94 LVI algorithms of OIpU(one-iteration-perupdate) type,to handle time-dependent QP(quadratic programming) problems subject to two constraints respectively(i.e.,equality and inequality constraints,equality and bound constraints,or inequality and bound constraints).Specifically,two "bridges" play essential parts of the methods(i.e.,the first "bridge" makes a QP problem convert to an LVI [linear variational inequality],and the second "bridge" makes the LVI convert to a PLPE [piecewise-linear projection equation]).On the basis of the standard94 LVI algorithm,the methods only update once through the solution of the previous sampling time ***,we conduct a number of experiments to substantiate the three algorithms respectively,which use exponential functions,log functions,and trigonometric functions in corresponding coefficients of the experimental examples.
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