human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "composition limits and separating examples for some boolean function complexity measures"
  Abstract: Block sensitivity ($bs(f)$), certificate complexity ($C(f)$) and fractional certificate complexity ($C^*(f)$) are three fundamental combinatorial measures of complexity of a boolean function $f$. It has long been known that $bs(f) \leq C^{\ast}(f) \leq C(f) =O(bs(f)^2)$. We provide an infinite family of examples for which $C(f)$ grows quadratically in $C^{\ast}(f)$ (and also $bs(f)$) giving optimal separations between these measures. Previously the biggest separation known was $C(f)=C^{\ast}(f)^{\log_{4.5}5}$. We also give a family of examples for which $C^{\ast}(f)=\Omega(bs(f)^{3/2})$. #R##N#These examples are obtained by composing boolean functions in various ways. Here the composition $f \circ g$ of $f$ with $g$ is obtained by substituting for each variable of $f$ a copy of $g$ on disjoint sets of variables. To construct and analyse these examples we systematically investigate the behaviour under function composition of these measures and also the sensitivity measure $s(f)$. The measures $s(f)$, $C(f)$ and $C^{\ast}(f)$ behave nicely under composition: they are submultiplicative (where measure $m$ is submultiplicative if $m(f \circ g) \leq m(f)m(g)$) with equality holding under some fairly general conditions. The measure $bs(f)$ is qualitatively different: it is not submultiplicative. This qualitative difference was not noticed in the previous literature and we correct some errors that appeared in previous papers. We define the composition limit of a measure $m$ at function $f$, $m^{\lim}(f)$ to be the limit as $k$ grows of $m(f^{(k)})^{1/k}$, where $f^{(k)}$ is the iterated composition of $f$ with itself $k$-times. For any function $f$ we show that $bs^{\lim}(f) = (C^*)^{\lim}(f)$ and characterize $s^{\lim}(f), (C^*)^{\lim}(f)$, and $C^{\lim}(f)$ in terms of the largest eigenvalue of a certain set of $2\times 2$ matrices associated with $f$.

Connected through hyperedge HE-1 (induced by source paper "a tight composition theorem for the randomized query complexity of partial functions"):
  with members:
    - "the power of many samples in query complexity"
    - "a new minimax theorem for randomized algorithms"
    - "optimal separation and strong direct sum for randomized query complexity"
    - "a composition theorem for randomized query complexity via max conflict complexity"
    - "a composition theorem for randomized query complexity"
    - "randomized query complexity of sabotaged and composed functions"
    - "separations in query complexity based on pointer functions"
    - "a composition theorem for decision tree complexity"

Connected through hyperedge HE-2 (induced by source paper "the power of many samples in query complexity"):
  with members:
    - "a composition theorem for decision tree complexity"

Connected through hyperedge HE-3 (induced by source paper "a composition theorem for randomized query complexity via max conflict complexity"):
  with members:
    - "a composition theorem via conflict complexity"
    - "conflict complexity is lower bounded by block sensitivity"
    - "on the randomised query complexity of composition"
    - "randomized query complexity of sabotaged and composed functions"
    - "a composition theorem for decision tree complexity"
    - "an optimal lower bound on the communication complexity of gap hamming distance"

Connected through hyperedge HE-4 (induced by source paper "all classical adversary methods are equivalent for total functions"):
  with members:
    - "randomized query complexity of sabotaged and composed functions"
    - "nearly optimal separations between communication or query complexity and partitions"

Connected through hyperedge HE-5 (induced by source paper "quadratically tight relations for randomized query complexity"):
  with members:
    - "nearly optimal separations between communication or query complexity and partitions"

Connected through hyperedge HE-6 (induced by source paper "low sensitivity functions from unambiguous certificates"):
  with members:
    - "randomized query complexity of sabotaged and composed functions"
    - "nearly optimal separations between communication or query complexity and partitions"
    - "degree and sensitivity tails of two distributions"
    - "separations in query complexity based on pointer functions"
    - "smooth boolean functions are easy efficient algorithms for low sensitivity functions"
    - "sensitivity versus certificate complexity of boolean functions"
    - "size of sets with small sensitivity a generalization of simon s lemma"
    - "an o n 0 4732 upper bound on the complexity of the gks communication game"

Connected through hyperedge HE-7 (induced by source paper "randomized query complexity of sabotaged and composed functions"):
  with members:
    - "nearly optimal separations between communication or query complexity and partitions"
    - "a quadratically tight partition bound for classical communication complexity and query complexity"
    - "a composition theorem for decision tree complexity"
    - "improved direct product theorems for randomized query complexity"
    - "optimal direct sum results for deterministic and randomized decision tree complexity"
    - "the partition bound for classical communication complexity and query complexity"

Connected through hyperedge HE-8 (induced by source paper "on the sensitivity conjecture for disjunctive normal forms"):
  with members:
    - "smooth boolean functions are easy efficient algorithms for low sensitivity functions"
    - "tighter relations between sensitivity and other complexity measures"
    - "new separation between s f and bs f"
    - "variations on the sensitivity conjecture"
    - "on the sensitivity of cyclically invariant boolean functions"

Question: Please tell me which class the center node 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)