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 "te eth lower bounds for qbfs of bounded treewidth"):
  Abstract: The problem of deciding the validity (QSAT) of quantified Boolean formulas (QBF) is a vivid research area in both theory and practice. In the field of parameterized algorithmics, the well-studied graph measure treewidth turned out to be a successful parameter. A well-known result by Chen in parameterized complexity is that QSAT when parameterized by the treewidth of the primal graph of the input formula together with the quantifier depth of the formula is fixed-parameter tractable. More precisely, the runtime of such an algorithm is polynomial in the formula size and exponential in the treewidth, where the exponential function in the treewidth is a tower, whose height is the quantifier depth. A natural question is whether one can significantly improve these results and decrease the tower while assuming the Exponential Time Hypothesis (ETH). In the last years, there has been a growing interest in the quest of establishing lower bounds under ETH, showing mostly problem-specific lower bounds up to the third level of the polynomial hierarchy. Still, an important question is to settle this as general as possible and to cover the whole polynomial hierarchy. In this work, we show lower bounds based on the ETH for arbitrary QBFs parameterized by treewidth (and quantifier depth). More formally, we establish lower bounds for QSAT and treewidth, namely, that under ETH there cannot be an algorithm that solves QSAT of quantifier depth i in runtime significantly better than i-fold exponential in the treewidth and polynomial in the input size. In doing so, we provide a versatile reduction technique to compress treewidth that encodes the essence of dynamic programming on arbitrary tree decompositions. Further, we describe a general methodology for a more fine-grained analysis of problems parameterized by treewidth that are at higher levels of the polynomial hierarchy.

Includes members:
  Member "treewidth and counting projected answer sets":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "structural decompositions of epistemic logic programs")
  Member "exploiting treewidth for projected model counting and its limits":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "exploiting database management systems and treewidth for counting")
  Member "counting complexity for reasoning in abstract argumentation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "answer set solving exploiting treewidth and its limits")
  Member "qbf as an alternative to courcelle s theorem":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "graph width measures for cnf encodings with auxiliary variables")
  Member "evaluating qbf solvers quantifier alternations matter":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "qratpre effective qbf preprocessing via strong redundancy properties")
  Member "slightly superexponential parameterized problems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on the complexity of finding large odd induced subgraphs and odd colorings")
  Member "parameterized complexity results for exact bayesian network structure learning":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "learning binary bayesian networks in polynomial time and sample complexity")
  Member "backdoors to tractable answer set programming":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "structural decompositions of epistemic logic programs")

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)