Yasuhiro Fujiwara, Makoto Nakatsuji, Hiroaki Shiokawa et al. · 2013
Graphs are a fundamental data structure and have been employed to model objects as well as their relationships. The similarity of objects on the web (e.g., webpages, photos, music, micro-blogs, and social networking service users) is the key to identifying relevant objects in many recent applications. SimRank, proposed by Jeh and Widom, provides a good similarity score and has been successfully used in many applications such as web spam detection, collaborative tagging analysis, link prediction, and so on. SimRank computes similarities iteratively, and it needs O(N <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sup> T) time and O(N <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ) space for similarity computation where N and T are the number of nodes and iterations, respectively. Unfortunately, this iterative approach is computationally expensive. The goal of this work is to process top-k search and range search efficiently for a given node. Our solution, SimMat, is based on two ideas: (1) It computes the approximate similarity of a selected node pair efficiently in non-iterative style based on the Sylvester equation, and (2) It prunes unnecessary approximate similarity computations when searching for the high similarity nodes by exploiting estimations based on the Cauchy-Schwarz inequality. These two ideas reduce the time and space complexities of the proposed approach to O(Nn) where n is the target rank of the low-rank approximation (n ≪ N in practice). Our experiments show that our approach is much faster, by several orders of magnitude, than previous approaches in finding the high similarity nodes.
Cited by 67
Eschenbach, Oliver · IEEE Transactions on Computers · 1978
The rotation of a graphic display through an angle δ requires a large number of multiplies by sin δ and cos δ. The time required for these multiplies can be reduced an order of magnitude or more by the appropriate choice of δ. The values chosen depend upon the base r and the digits of accuracy d.
Cited by 2
R. Sivaraj, T. Ravichandran · International Journal of Computer Applications · 2011
Genetic algorithm is an intelligent way for solving combinatorial, NP hard problems and many other problems which cannot be easily solved by applying traditional mathematical formula. The proposed method gives a new variant of the Standard Genetic algorithm which is very simple and will easily find the solution even for complex problems. It implements the concept of grouping to reach the optimal solution. The selection pressure which is a crucial factor that determines the efficiency of the algorithm is very much reduced in the proposed algorithm. The convergence velocity of the algorithm is greatly improved thereby reducing the time taken for the algorithm to reach the solution.
Cited by 8Open access
Ashish Saxena · 2018
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Xiaoqing Liu, Junguk L. Kim · Information Processing Letters · 1992
Cited by 1
Azzam Sleit, Wesam Almobaideen, Aladdin Baarah et al. · Journal of Applied Sciences · 2007
Cited by 13
Farrokh Neghabat · Operations Research · 1974
This paper treats the problem of locating a given number of interrelated physical facilities in a single- or multi-story building as an optimization model such that the weighted sum of the distances along orthogonal directions is minimized, and describes a constructive heuristic algorithm for the one-dimensional model. This linear placement algorithm is then extended to higher dimensions for placing uniform-size equipment modules at homogeneous fixed locations. The algorithm accommodates lower-bound constraints for the linear case efficiently and produces near-optimal solutions. Its significance, as demonstrated by comparison with some existing heuristic procedures, is that it has the capability of handling efficiently problems with large numbers of equal-size facilities whose solutions are computationally intractable using the present optimum-producing methods.
Cited by 46
Tetsuya Izu, Jun Kogure, Masayuki Noro et al. · Lecture notes in computer science · 1998
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RECERCAT (Consorci de Serveis Universitaris de Catalunya) · 2018
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Muntasir Raihan Rahman, MD. EHTESAMUL HAQUE , et al. · 2008
An edge-ranking of a graph G is a labeling of the edges of G with positive integers such that every path between two edges with the same label γ contains an edge with label λ&gt; γ. In the on-line edge-ranking model the edges e1, e2..., em arrive one at a time in any order, where m is the number of edges in the graph. Only the partial information in the induced subgraph G[{e1, e2,..., ei}] is available when the algorithm must choose a rank for ei. In this paper, we present an on-line algorithm for ranking the edges of a tree in time O(n 2), where n is the number of vertices in the tree.
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Jörg Holfeld, Gerhard Fettweis · Cambridge University Press eBooks · 2011
In this chapter, we now look into algorithm implementation aspects connected to CoMP. In Section 10.1, the issue of numerically robust and flexible multicell precoding is addressed, while Section 10.2 looks into the performance of interference rejection combining filters under practical conditions.
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Sergey V. Burtsev, Ye.P. Kuzmin · Computers & Graphics · 1993
Cited by 81
Qinsheng Du, Jian Zhao, Lijuan Shi et al. · 2012
The marching cubes (MC) algorithm is a typical representative for surface reconstruction method. However, there are still some shortcomings about the topology structure and the represent accuracy of the isosurfaces which are extracted by the MC algorithm. For the high execution efficiency, the improved MC algorithm is proposed and implemented in the visualization tool kit (VTK) according to the isosurfaces continuity in the cubes. A new 3D reconstruction jaw system for the speech rehabilitation is developed based on the improved MC algorithm. The experiment showed that the improved MC algorithm is efficient and robust.
Cited by 2
Ji Liu, Huiyang Zhou · arXiv (Cornell University) · 2021
Quantum computing has noteworthy speedup over classical computing by taking advantage of quantum parallelism, i.e., the superposition of states. In particular, quantum search is widely used in various computationally hard problems. Grover's search algorithm finds the target element in an unsorted database with quadratic speedup than classical search and has been proved to be optimal in terms of the number of queries to the database. The challenge, however, is that Grover's search algorithm leads to high numbers of quantum gates, which make it infeasible for the Noise-Intermediate-Scale-Quantum (NISQ) computers. In this paper, we propose a novel hardware efficient quantum search algorithm to overcome this challenge. Our key idea is to replace the global diffusion operation with low-cost local diffusions. Our analysis shows that our algorithm has similar oracle complexity to the original Grover's search algorithm while significantly reduces the circuit depth and gate count. The circuit cost reduction leads to a remarkable improvement in the system success rates, paving the way for quantum search on NISQ machines.
Cited by 7Open access
Pan Hong-yan · 2009
As a step forward to analyzing patterns in sequences, we introduce the problem of mining closed repetitive gapped subsequences and propose efficient solutions. Given a database of sequences where each sequence is an ordered list of events, the pattern we would like to mine is called repetitive gapped subsequence. Different from the sequential pattern mining problem, repetitive support captures not only repetitions of a pattern in different sequences but also the repetitions within a sequence. Given a users-specified support threshold min_sup, we study finding the set of all patterns with repetitive support no less than min_sup. To obtain a compact yet complete result set and improve the efficiency, we also study finding closed patterns. Efficient mining algorithms to find the complete set of desired patterns are proposed based on the idea of instance growth. Our performance study on various datasets shows the efficiency of our approach. A case study is also performed to show the utility of our approach.
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Shi-JimYen, Tsan-ChengSu, Shun-ChinHsu · Medical Entomology and Zoology · 2010
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Shin, Jinwoo · DSpace@MIT (Massachusetts Institute of Technology) · 2010
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mathematics, 2010.
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Raphael A. Finkel, Hari Madduri · Information Processing Letters · 1987
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Haiou Qin, Du Zhang, Xibin Sun et al. · International Journal of Artificial Intelligence Tools · 2019
One of the emerging research opportunities in machine learning is to develop computing systems that learn many tasks continuously and improve the performance of learned tasks incrementally over time. In real world, learners have to adapt to labeled and unlabeled samples from various tasks which arrive randomly. In this paper, we propose an efficient algorithm called Efficient Perpetual Learning Algorithm (EPLA) which is suitable for learning multiple tasks in both offline and online settings. The algorithm, which is an extension of ELLA,4 is part of what we call perpetual learning that can learn new tasks or refine knowledge of learned tasks for improved performance with newly arrived labeled samples in an incremental fashion. Several salient features exist for EPLA. The learning episodes are triggered via either extrinsic or intrinsic stimuli. Agent systems based on the proposed algorithm can be engaged in an open-ended and alternating sequence of learning episodes and working episodes. Unlabeled samples can be used to self-train the learner in small data setting. Compared with ELLA, EPLA shows almost equivalent performance without memorizing any labeled samples learned previously.
Cited by 1
Yuepeng Ding, Xiong Xie, Bo Jiang · Springer Link (Chiba Institute of Technology) · 2018
\nThis paper proposed an intelligent algorithm, which can build the shortest path of the intersecting circle sequences in the plane. The problem is transformed to a corresponding problem of computing the shortest path of three disjoint circles. And it is also an in-depth study of the traversal problem for the disjoint circle sequences. On the basis of the previous work, the algorithms are developed to construct such shortest path in polynomial time of O(kn) where 1≤k≤n under a given computational threshold. Since the algorithm is fully polynomial time consuming, this work can be conducted in layered manufacturing of rapid prototyping, displacement of wireless sensor networks, or other related computer-aided design and manufacturing applications. \n
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