scholarly journals A Polynomial Kernel for Distance-Hereditary Vertex Deletion

Algorithmica ◽  
2021 ◽  
Author(s):  
Eun Jung Kim ◽  
O-joung Kwon
Author(s):  
Junjie Luo ◽  
Hendrik Molter ◽  
Ondřej Suchý

AbstractWe study the -hard graph problem Collapsed k-Core where, given an undirected graph G and integers b, x, and k, we are asked to remove b vertices such that the k-core of remaining graph, that is, the (uniquely determined) largest induced subgraph with minimum degree k, has size at most x. Collapsed k-Core was introduced by Zhang et al. (2017) and it is motivated by the study of engagement behavior of users in a social network and measuring the resilience of a network against user drop outs. Collapsed k-Core is a generalization of r-Degenerate Vertex Deletion (which is known to be -hard for all r ≥ 0) where, given an undirected graph G and integers b and r, we are asked to remove b vertices such that the remaining graph is r-degenerate, that is, every its subgraph has minimum degree at most r. We investigate the parameterized complexity of Collapsed k-Core with respect to the parameters b, x, and k, and several structural parameters of the input graph. We reveal a dichotomy in the computational complexity of Collapsed k-Core for k ≤ 2 and k ≥ 3. For the latter case it is known that for all x ≥ 0 Collapsed k-Core is -hard when parameterized by b. For k ≤ 2 we show that Collapsed k-Core is -hard when parameterized by b and in when parameterized by (b + x). Furthermore, we outline that Collapsed k-Core is in when parameterized by the treewidth of the input graph and presumably does not admit a polynomial kernel when parameterized by the vertex cover number of the input graph.


Algorithmica ◽  
2016 ◽  
Vol 79 (1) ◽  
pp. 66-95 ◽  
Author(s):  
Mamadou Moustapha Kanté ◽  
Eun Jung Kim ◽  
O-joung Kwon ◽  
Christophe Paul

2013 ◽  
Vol 27 (4) ◽  
pp. 1964-1976 ◽  
Author(s):  
Fedor V. Fomin ◽  
Saket Saurabh ◽  
Yngve Villanger

Author(s):  
Akanksha Agrawal ◽  
Pranabendu Misra ◽  
Saket Saurabh ◽  
Meirav Zehavi

Author(s):  
Hedieh Sajedi ◽  
Mehran Bahador

In this paper, a new approach for segmentation and recognition of Persian handwritten numbers is presented. This method utilizes the framing feature technique in combination with outer profile feature that we named this the adapted framing feature. In our proposed approach, segmentation of the numbers into digits has been carried out automatically. In the classification stage of the proposed method, Support Vector Machines (SVM) and k-Nearest Neighbors (k-NN) are used. Experimentations are conducted on the IFHCDB database consisting 17,740 numeral images and HODA database consisting 102,352 numeral images. In isolated digit level on IFHCDB, the recognition rate of 99.27%, is achieved by using SVM with polynomial kernel. Furthermore, in isolated digit level on HODA, the recognition rate of 99.07% is achieved by using SVM with polynomial kernel. The experiments illustrate that applying our proposed method resulted higher accuracy compared to previous researches.


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