human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "lower bounds for the parameterized complexity of minimum fill in and other completion problems"):
  Abstract: In this work, we focus on several completion problems for subclasses of chordal graphs: Minimum Fill-In, Interval Completion, Proper Interval Completion, Threshold Completion, and Trivially Perfect Completion. In these problems, the task is to add at most k edges to a given graph in order to obtain a chordal, interval, proper interval, threshold, or trivially perfect graph, respectively. We prove the following lower bounds for all these problems, as well as for the related Chain Completion problem: Assuming the Exponential Time Hypothesis, none of these problems can be solved in time 2^O(n^(1/2) / log^c n) or 2^O(k^(1/4) / log^c k) n^O(1), for some integer c. Assuming the non-existence of a subexponential-time approximation scheme for Min Bisection on d-regular graphs, for some constant d, none of these problems can be solved in time 2^o(n) or 2^o(sqrt(k)) n^O(1). #R##N#For all the aforementioned completion problems, apart from Proper Interval Completion, FPT algorithms with running time of the form 2^O(sqrt(k) log k) n^O(1) are known. Thus, the second result proves that a significant improvement of any of these algorithms would lead to a surprising breakthrough in the design of approximation algorithms for Min Bisection. #R##N#To prove our results, we use a reduction methodology based on combining the classic approach of starting with a sparse instance of 3-Sat, prepared using the Sparsification Lemma, with the existence of almost linear-size Probabilistically Checkable Proofs (PCPs). Apart from our main results, we also obtain lower bounds excluding the existence of subexponential algorithms for the Optimum Linear Arrangement problem, as well as improved, yet still not tight, lower bounds for Feedback Arc Set in Tournaments.

Includes members:
  Member "time approximation trade offs for inapproximable problems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "improved in approximability bounds for d scattered set")
  Member "on the threshold of intractability":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "faster and enhanced inclusion minimal cograph completion")
  Member "a polynomial kernel for trivially perfect editing":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "unit interval vertex deletion fewer vertices are relevant")
  Member "a subexponential parameterized algorithm for proper interval completion":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "approximation and kernelization for chordal vertex deletion")
  Member "a subexponential parameterized algorithm for interval completion":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "polynomial kernelization for removing induced claws and diamonds")
  Member "sparsification and subexponential approximation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "new tools and connections for exponential time approximation")
  Member "exploring subexponential parameterized complexity of completion problems":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "polynomial kernelization for removing induced claws and diamonds")
  Member "parameterized in approximability of subset problems":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "parameterized approximation schemes using graph widths")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.CC(Computational Complexity)