Efficient Deployment of Base Stations in Wireless Communication Networks by Li, Zimao, Wang, Yingying, Ma, Maode

“…In this paper, we improve the time complexity of the approximation algorithms and conduct simulations to demonstrate the validness of our improvements.…”
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Quantum computational phase transition in combinatorial problems by Bingzhi Zhang, Akira Sone, Quntao Zhuang

“…Then, we show that the high problem density region, which limits QAOA’s performance in hard optimization problems (reachability deficits), is actually a good place to utilize QAOA: its approximation ratio has a much slower decay with the problem density, compared to classical approximate algorithms. Indeed, it is exactly in this region that quantum advantages of QAOA over classical approximate algorithms can be identified.…”
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Time−Bounded Verification of CTMCs Against Real−Time Specifications by Chen, T, Diciolla, M, Kwiatkowska, M, Mereacre, A

“…For MTL, we consider both the continuous and the pointwise semantics. The approximation algorithms differ mainly in constraints generation for the two types of specifications.…”

An Approximate Cone Beam Reconstruction Algorithm for Gantry-Tilted CT Using Tangential Filtering by Ming Yan, Cishen Zhang, Hongzhu Liang

“…FDK algorithm is a well-known 3D (three-dimensional) approximate algorithm for CT (computed tomography) image reconstruction and is also known to suffer from considerable artifacts when the scanning cone angle is large. …”
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MULTIPLE-PURPOSE SOLUTION TO HOMOGENEOUS ALLOCATION PROBLEMS BASED ON MODIFIED ROMANOVSKY ALGORITHM AND SELECTIVE-PERMUTATION ALGORITHM by Rudolf A. Neydorf, Artem A. Zhikulin

“…The comparative analysis with such approximate algorithms as the critical pat h technique (CPT) and the evolutional genetic algorithm (EGA) is carried out. …”
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MULTIPLE-PURPOSE SOLUTION TO HOMOGENEOUS ALLOCATION PROBLEMS BASED ON MODIFIED ROMANOVSKY ALGORITHM AND SELECTIVE-PERMUTATION ALGORITHM by Rudolf A. Neydorf, Artem A. Zhikulin

“…The comparative analysis with such approximate algorithms as the critical pat h technique (CPT) and the evolutional genetic algorithm (EGA) is carried out. …”
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Performance Comparisons of Greedy Algorithms in Compressed Sensing by Blanchard, J, Tanner, J

“…Compressed sensing has motivated the development of numerous sparse approximation algorithms designed to return a solution to an underdetermined system of linear equations where the solution has the fewest number of nonzeros possible, referred to as the sparsest solution. …”

Hierarchical MEC Servers Deployment and User-MEC Server Association in C-RANs over WDM Ring Networks by Zhen Liu, Jiawei Zhang, Yanan Li, Yuefeng Ji

“…In terms of the MINLP model, we then propose an enumeration algorithm and approximate algorithm based on the improved entropy weight and TOPSIS methods. …”
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Local clustering via approximate heat kernel PageRank with subgraph sampling by Zhenqi Lu, Johan Wahlström, Arye Nehorai

“…But computing an exact heat kernel PageRank vector may be expensive, and approximate algorithms are often used instead. Most approximate algorithms compute the heat kernel PageRank vector on the whole graph, and thus are dependent on global structures. …”
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Fast mixing via polymers for random graphs with unbounded degree by Galanis, A, Goldberg, L, Stewart, J

“…<p>The polymer model framework is a classical tool from statistical mechanics that has recently been used to obtain approximation algorithms for spin systems on classes of bounded-degree graphs; examples include the ferromagnetic Potts model on expanders and on the grid. …”

Fast mixing via polymers for random graphs with unbounded degree by Galanis, A, Goldberg, L, Stewart, J

“…The polymer model framework is a classical tool from statistical mechanics that has recently been used to obtain approximation algorithms for spin systems on classes of bounded-degree graphs; examples include the ferromagnetic Potts model on expanders and on the grid. …”

Analytical and numerical approach for a nonlinear Volterra-Fredholm integro-differential equation by Mohammed Charif Bounaya, Samir Lemita, Sami Touati, Mohamed Zine Aissaoui

“…The approximation of the solution is performed using Nystrom method in conjunction with successive approximations algorithm. Finally, we give a numerical example, in order to verify the effectiveness of the proposed method with respect to the analytical study. …”
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Conjugate Gradient Iterative Hard Thresholding: Observed Noise Stability for Compressed Sensing by Blanchard, J, Tanner, J, Wei, K

“…Conjugate Gradient Iterative Hard Thresholding (CGIHT) for compressed sensing combines the low per iteration complexity of fast greedy sparse approximation algorithms with the improved convergence rates of more complicated, projection based algorithms. …”

Contribution to the Chebyshev Approximations of the Normalized Low-Pass Prototype by J. Vrbata, M. Vlcek, M. Laipert

“…The standard approximation algorithms are well described in theliterature, but some equiripple approximations are described with somedeficiencies. …”
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Blocks for two-machines total weighted tardiness flow shop scheduling problem by W. Bożejko, M. Uchroński, M. Wodecki

“…We propose the introduction of new elimination block properties allowing for accelerating the operation of approximate algorithms of local searches, solving this problem and improving the quality of solutions determined by them.…”
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Token Swapping on Trees by Ahmad Biniaz, Kshitij Jain, Anna Lubiw, Zuzana Masárová, Tillmann Miltzow, Debajyoti Mondal, Anurag Murty Naredla, Josef Tkadlec, Alexi Turcotte

“…Furthermore, the two best-known 2-approximation algorithms have approximation factor exactly 2. 3. …”
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Perturbation stability for approximate MAP inference by Lang, Hunter(Hunter J.)

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Minimizing the Diameter of a Network Using Shortcut Edges by Demaine, Erik D., Zadimoghaddam, Morteza

“…We develop constant-factor approximation algorithms for different variations of this problem. …”
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A Trade-Off Algorithm for Solving p-Center Problems with a Graph Convolutional Network by Haojian Liang, Shaohua Wang, Huilai Li, Huichun Ye, Yang Zhong

“…This study implements two methods to solve this problem: an exact algorithm and an approximate algorithm. Exact algorithms can get the optimal solution to the problem, but they are inefficient and time-consuming. …”
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Performance comparisons of greedy algorithms in compressed sensing by Blanchard, J, Tanner, J

“…Compressed sensing has motivated the development of numerous sparse approximation algorithms designed to return a solution to an underdetermined system of linear equations where the solution has the fewest number of nonzeros possible, referred to as the sparsest solution. …”