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Bundit Laekhanukit
Researcher at Shanghai University of Finance and Economics
Publications - 59
Citations - 723
Bundit Laekhanukit is an academic researcher from Shanghai University of Finance and Economics. The author has contributed to research in topics: Approximation algorithm & Steiner tree problem. The author has an hindex of 15, co-authored 56 publications receiving 663 citations. Previous affiliations of Bundit Laekhanukit include Weizmann Institute of Science & Shanghai University.
Papers
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Proceedings ArticleDOI
From Gap-ETH to FPT-Inapproximability: Clique, Dominating Set, and More
Parinya Chalermsook,Marek Cygan,Guy Kortsarz,Bundit Laekhanukit,Pasin Manurangsi,Danupon Nanongkai,Luca Trevisan +6 more
TL;DR: In particular, Chen et al. as mentioned in this paper showed that there is no O(opt)-FPT-approximation algorithm for Clique and no f-opt-FPT algorithm for DomSet, for any function f (e.g., this holds even if f is an exponential or the Ackermann function).
Proceedings ArticleDOI
Independent Set, Induced Matching, and Pricing: Connections and Tight (Subexponential Time) Approximation Hardnesses
TL;DR: A new PCP is constructed that is sparse and has nearly-linear size, large degree, and small free-bit complexity and follows from nearly tight subexponential time inapproximability of the first problem, illustrating a rare application of the second type of inapp approximability result to the first one.
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Graph Products Revisited: Tight Approximation Hardness of Induced Matching, Poset Dimension and More
TL;DR: In this paper, the authors studied graph products in the following non-standard form: $f((G\oplus H)*J)$ where $G$, $H$ and $J$ are two different graph products and $f$ is a graph property.
Proceedings ArticleDOI
Graph products revisited: tight approximation hardness of induced matching, poset dimension and more
TL;DR: Tight hardness of approximation is obtained for various problems in discrete mathematics and computer science: bipartite induced and semi-induced matching, poset dimension, maximum feasible subsystem with 0/1 coefficients, unit-demand min-buying and single-minded pricing, donation center location, boxicity, cubicity, threshold dimension and independent packing.
Posted Content
On the Parameterized Complexity of Approximating Dominating Set
TL;DR: In this paper, the authors studied the parameterized complexity of approximating the dominating set problem and showed that there is no FPT-approximation algorithm for the problem with complexity at most O(k) for any constant k > 0.