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 "co nondeterminism in compositions a kernelization lower bound for a ramsey type problem"):
  Abstract: Until recently, techniques for obtaining lower bounds for kernelization were one of the most sought after tools in the field of parameterized complexity. Now, after a strong influx of techniques, we are in the fortunate situation of having tools available that are even stronger than what has been required in their applications so far. Based on a result of Fortnow and Santhanam (JCSS 2011), Bodlaender et al. (JCSS 2009) showed that, unless NP \subseteq coNP/poly, the existence of a deterministic polynomial-time composition algorithm, i.e., an algorithm which outputs an instance of bounded parameter value which is yes if and only if one of t input instances is yes, rules out the existence of polynomial kernels for a problem. Dell and van Melkebeek (STOC 2010) continued this line of research and, amongst others, were able to rule out kernels of size O(k^d-eps) for certain problems, assuming NP !\subseteq coNP/poly. Their work implies that even the existence of a co-nondeterministic composition rules out polynomial kernels. #R##N#In this work we present the first example of how co-nondeterminism can help to make a composition algorithm. We study a Ramsey-type problem: Given a graph G and an integer k, the question is whether G contains an independent set or a clique of size at least k. It was asked by Rod Downey whether this problem admits a polynomial kernelization. We provide a co-nondeterministic composition based on embedding t instances into a single host graph H. The crux is that the host graph H needs to observe a bound of L \in O(log t) on both its maximum independent set and maximum clique size, while also having a cover of its vertex set by independent sets and cliques all of size L; the co-nondeterministic composition is build around the search for such graphs. Thus we show that, unless NP \subseteq coNP/poly, the problem does not admit a kernelization with polynomial size guarantee.

Includes members:
  Member "kernelization of packing problems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the approximate compressibility of connected vertex cover")
  Member "cross composition a new technique for kernelization lower bounds":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "parameterized coloring problems on threshold graphs")
  Member "preprocessing of min ones problems a dichotomy":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "optimal polynomial time compression for boolean max csp")
  Member "kernel s for problems with no kernel on out trees with many leaves":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a polynomial turing kernel for weighted independent set in bull free 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.DS(Data Structures and Algorithms)