Search Results - Computer Science - Data Structures and Algorithms

SciPy 1.0: fundamental algorithms for scientific computing in Python by Virtanen, Pauli, Gommers, Ralf, Oliphant, Travis E., Haberland, Matt, Reddy, Tyler, Cournapeau, David, Burovski, Evgeni, Peterson, Pearu, Weckesser, Warren, Bright, Jonathan, van der Walt, Stéfan J., Brett, Matthew, Wilson, Joshua, Millman, K. Jarrod, Mayorov, Nikolay, Nelson, Andrew R. J., Jones, Eric, Kern, Robert, Larson, Eric, Carey, C J, Polat, İlhan, Feng, Yu, Moore, Eric W., VanderPlas, Jake, Laxalde, Denis, Perktold, Josef, Cimrman, Robert, Henriksen, Ian, Quintero, E. A., Harris, Charles R., Archibald, Anne M., Ribeiro, Antônio H., Pedregosa, Fabian, van Mulbregt, Paul

“… Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages…”
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Approximate Counting for Spin Systems in Sub-Quadratic Time by Anand, Konrad, Feng, Weiming, Freifeld, Graham, Guo, Heng, Wang, Jiaheng

“…We present two randomised approximate counting algorithms with$\widetilde{O}(n^{2-c}/\varepsilon^2)$running time for some constant…”
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Testing Distributions of Huge Objects by Goldreich, Oded, Ron, Dana

“…We initiate a study of a new model of property testing that is a hybrid of testing properties of distributions and testing properties of strings. Specifically,…”
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Lettericity of graphs: an FPT algorithm and a bound on the size of obstructions by Alecu, Bogdan, Kanté, Mamadou Moustapha, Lozin, Vadim, Zamaraev, Viktor

“… However, no constructive algorithms and no specific bounds on the size of forbidden graphs are available up to date…”
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A Refined Laser Method and Faster Matrix Multiplication by Alman, Josh, Williams, Virginia Vassilevska

“… the `value' of a tensor in designing matrix multiplication algorithms. The main result of this paper is a refinement of the laser method that improves the resulting value bound for most sufficiently large tensors…”
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Introduction to local certification by Feuilloley, Laurent

“…A distributed graph algorithm is basically an algorithm where every node of a graph can look at its neighborhood at some distance in the graph and chose its output…”
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Fully Dynamic Connectivity in$O(\log n(\log\log n)^2)$Amortized Expected Time by Huang, Shang-En, Huang, Dawei, Kopelowitz, Tsvi, Pettie, Seth, Thorup, Mikkel

“… We present a randomized Las Vegas dynamic connectivity data structure with$O(\log n(\log\log n)^2)$amortized expected update time…”
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Approximating Maximum Edge 2-Coloring by Normalizing Graphs by Mömke, Tobias, Popa, Alexandru, Roshany-Tabrizi, Aida, Ruderer, Michael, Vincze, Roland

“… For the problem a 2-approximation algorithm is known, and if the input graph has a perfect matching, the same algorithm has been shown to have a performance guarantee of 5/3…”
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Brooks' Theorem in Graph Streams: A Single-Pass Semi-Streaming Algorithm for$\Delta$ -Coloring by Assadi, Sepehr, Kumar, Pankaj, Mittal, Parth

“…Every graph with maximum degree$\Delta$can be colored with$(\Delta+1)$colors using a simple greedy algorithm…”
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Strongly Sublinear Algorithms for Testing Pattern Freeness by Newman, Ilan, Varma, Nithin

“… (Random Structures and Algorithms 2019). We show that for all constants$k \in \mathbb{N}$ ,$\varepsilon \in (0,1)$ , and permutation$\pi:[k] \to [k]$ , there is a…”
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Simpler and Unified Recognition Algorithm for Path Graphs and Directed Path Graphs by Balzotti, Lorenzo

“… Our algorithm does not require complex data structures and has an easy and intuitive implementation, simplifying recognition algorithms for both graph classes. Comment…”
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Polynomial kernels for edge modification problems towards block and strictly chordal graphs by Dumas, Maël, Perez, Anthony, Rocton, Mathis, Todinca, Ioan

“…We consider edge modification problems towards block and strictly chordal graphs, where one is given an undirected graph$G = (V,E)$and an integer$k \in…”
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On Approximability of Steiner Tree in$\ell_p$ -metrics by Fleischmann, Henry, Gavva, Surya Teja, S, Karthik C.

“…In the Continuous Steiner Tree problem (CST), we are given as input a set of points (called terminals) in a metric space and ask for the minimum-cost tree…”
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A Practical Algorithm with Performance Guarantees for the Art Gallery Problem by Hengeveld, Simon, Miltzow, Tillmann

“… in$P$ . The art gallery problem seeks a minimum size set$G\subset P$of guards that sees$P$completely. The only currently correct algorithm to solve the art gallery problem exactly uses algebraic methods and is attributed to Sharir…”
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Constant-delay enumeration for SLP-compressed documents by Muñoz, Martín, Riveros, Cristian

“… This model extends the notion of Regular Spanners as it allows arbitrarily long outputs. Our main result is an algorithm that evaluates such a query by enumerating…”
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A tree structure for dynamic facility location by Henzinger, Monika, Leniowski, Dariusz, Mathieu, Claire

“…In this paper, we study the problem of dynamic facility location. We maintain a solution with cost O(1) times the cost of an optimal solution in metric spaces…”
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Fine-grained Meta-Theorems for Vertex Integrity by Lampis, Michael, Mitsou, Valia

“…Vertex Integrity is a graph measure which sits squarely between two more well-studied notions, namely vertex cover and tree-depth, and that has recently gained…”
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On-line algorithms for multiplication and division in real and complex numeration systems by Frougny, Christiane, Pavelka, Marta, Pelantova, Edita, Svobodova, Milena

“… An on-line algorithm processes the input piece-by-piece in a serial fashion. On-line arithmetic, introduced by Trivedi and Ercegovac, is a mode of computation…”
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PPSZ is better than you think by Scheder, Dominik

“…PPSZ, for long time the fastest known algorithm for$k$ -SAT, works by going through the variables of the input formula in random order…”
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A$(3+\varepsilon)$ -Approximate Correlation Clustering Algorithm in Dynamic Streams by Cambus, Mélanie, Kuhn, Fabian, Lindy, Etna, Pai, Shreyas, Uitto, Jara

“…Grouping together similar elements in datasets is a common task in data mining and machine learning…”
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