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: "tighter relations between sensitivity and other complexity measures"
  Abstract: Sensitivity conjecture is a longstanding and fundamental open problem in the area of complexity measures of Boolean functions and decision tree complexity. The conjecture postulates that the maximum sensitivity of a Boolean function is polynomially related to other major complexity measures. Despite much attention to the problem and major advances in analysis of Boolean functions in the past decade, the problem remains wide open with no positive result toward the conjecture since the work of Kenyon and Kutin from 2004. #R##N#In this work, we present new upper bounds for various complexity measures in terms of sensitivity improving the bounds provided by Kenyon and Kutin. Specifically, we show that deg(f)^{1-o(1)}=O(2^{s(f)}) and C(f) < 2^{s(f)-1} s(f); these in turn imply various corollaries regarding the relation between sensitivity and other complexity measures, such as block sensitivity, via known results. The gap between sensitivity and other complexity measures remains exponential but these results are the first improvement for this difficult problem that has been achieved in a decade.

Connected through hyperedge HE-1 (induced by source paper "sensitivity conjecture and log rank conjecture for functions with small alternating numbers"):
  with members:
    - "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"
    - "parity decision tree complexity and 4 party communication complexity of xor functions are polynomially equivalent"
    - "learning circuits with few negations"
    - "a composition theorem for parity kill number"
    - "communication is bounded by root of rank"
    - "fourier sparsity spectral norm and the log rank conjecture"

Connected through hyperedge HE-2 (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-3 (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"
    - "composition limits and separating examples for some boolean function complexity measures"
    - "new separation between s f and bs f"
    - "variations on the sensitivity conjecture"
    - "on the sensitivity of cyclically invariant boolean functions"

Connected through hyperedge HE-4 (induced by source paper "degree and sensitivity tails of two distributions"):
  with members:
    - "smooth boolean functions are easy efficient algorithms for low sensitivity functions"
    - "size of sets with small sensitivity a generalization of simon s lemma"
    - "representation learning a review and new perspectives"

Connected through hyperedge HE-5 (induced by source paper "smooth boolean functions are easy efficient algorithms for low sensitivity functions"):
  with members:
    - "sensitivity versus certificate complexity of boolean functions"
    - "size of sets with small sensitivity a generalization of simon s lemma"
    - "a tight lower bound on certificate complexity in terms of block sensitivity and sensitivity"
    - "analysis of boolean functions"
    - "new separation between s f and bs f"
    - "variations on the sensitivity conjecture"

Connected through hyperedge HE-6 (induced by source paper "sensitivity versus certificate complexity of boolean functions"):
  with members:
    - "size of sets with small sensitivity a generalization of simon s lemma"
    - "new separation between s f and bs f"
    - "sensitivity versus block sensitivity of boolean functions"

Connected through hyperedge HE-7 (induced by source paper "size of sets with small sensitivity a generalization of simon s lemma"):
  with members:
    - "new separation between s f and bs f"
    - "sensitivity versus block sensitivity of boolean functions"

Connected through hyperedge HE-8 (induced by source paper "a tight lower bound on certificate complexity in terms of block sensitivity and sensitivity"):
  with members:
    - "new separation between s f and bs f"
    - "variations on the sensitivity conjecture"
    - "sensitivity versus block sensitivity of 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)