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 "optimal sparsification for some binary csps using low degree polynomials"):
  Abstract: This paper analyzes to what extent it is possible to efficiently reduce the number of clauses in NP-hard satisfiability problems, without changing the answer. Upper and lower bounds are established using the concept of kernelization. Existing results show that if NP is not contained in coNP/poly, no efficient preprocessing algorithm can reduce n-variable instances of CNF-SAT with d literals per clause, to equivalent instances with $O(n^{d-e})$ bits for any e > 0. For the Not-All-Equal SAT problem, a compression to size $\~O(n^{d-1})$ exists. We put these results in a common framework by analyzing the compressibility of binary CSPs. We characterize constraint types based on the minimum degree of multivariate polynomials whose roots correspond to the satisfying assignments, obtaining (nearly) matching upper and lower bounds in several settings. Our lower bounds show that not just the number of constraints, but also the encoding size of individual constraints plays an important role. For example, for Exact Satisfiability with unbounded clause length it is possible to efficiently reduce the number of constraints to n+1, yet no polynomial-time algorithm can reduce to an equivalent instance with $O(n^{2-e})$ bits for any e > 0, unless NP is a subset of coNP/poly.

Includes members:
  Member "optimal data reduction for graph coloring using low degree polynomials":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "parameterized complexity of conflict free graph coloring")
  Member "best case and worst case sparsifiability of boolean csps":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "sparsification of binary csps")
  Member "kernelization of constraint satisfaction problems a study through universal algebra":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "optimal polynomial time compression for boolean max csp")
  Member "complexity and approximability of parameterized max csps":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "parameterized compilation lower bounds for restricted cnf formulas")
  Member "sparsification upper and lower bounds for graph problems and not all equal sat":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "optimal polynomial time compression for boolean max csp")
  Member "nonclassical polynomials as a barrier to polynomial lower bounds":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "torus polynomials an algebraic approach to acc lower bounds")
  Member "on sparsification for computing treewidth":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "best case and worst case sparsifiability of boolean csps")
  Member "kernelization lower bounds by cross composition":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "subexponential parameterized algorithms and kernelization on almost chordal graphs")

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)