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: "an approximation algorithm for approximation rank"
  Abstract: One of the strongest techniques available for showing lower bounds on quantum communication complexity is the logarithm of the approximation rank of the communication matrix--the minimum rank of a matrix which is entrywise close to the communication matrix. This technique has two main drawbacks: it is difficult to compute, and it is not known to lower bound quantum communication complexity with entanglement. #R##N#Linial and Shraibman recently introduced a norm, called gamma_2^{alpha}, to quantum communication complexity, showing that it can be used to lower bound communication with entanglement. Here the parameter alpha is a measure of approximation which is related to the allowable error probability of the protocol. This bound can be written as a semidefinite program and gives bounds at least as large as many techniques in the literature, although it is smaller than the corresponding alpha-approximation rank, rk_alpha. We show that in fact log gamma_2^{alpha}(A)$ and log rk_{alpha}(A)$ agree up to small factors. As corollaries we obtain a constant factor polynomial time approximation algorithm to the logarithm of approximate rank, and that the logarithm of approximation rank is a lower bound for quantum communication complexity with entanglement.

Connected through hyperedge HE-1 (induced by source paper "a new minimax theorem for randomized algorithms"):
  with members:
    - "the power of many samples in query complexity"
    - "a tight composition theorem for the randomized query complexity of partial functions"
    - "optimal separation and strong direct sum for randomized query complexity"
    - "strong direct product theorems for quantum communication and query complexity"

Connected through hyperedge HE-2 (induced by source paper "on the complexity of opinions and online discussions"):
  with members:
    - "deep sentence embedding using long short term memory networks analysis and application to information retrieval"
    - "learning and forecasting opinion dynamics in social networks"
    - "the complexity of computing the minimum rank of a sign pattern matrix"
    - "distributed representations of sentences and documents"
    - "controversy and sentiment in online news"
    - "convolutional neural networks for sentence classification"

Connected through hyperedge HE-3 (induced by source paper "a nearly optimal lower bound on the approximate degree of ac 0"):
  with members:
    - "on szk and pp"
    - "separations in query complexity based on pointer functions"
    - "dual polynomials for collision and element distinctness"
    - "distribution independent reliable learning"
    - "dual lower bounds for approximate degree and markov bernstein inequalities"
    - "faster private release of marginals on small databases"
    - "hardness amplification and the approximate degree of constant depth circuits"
    - "faster algorithms for privately releasing marginals"

Connected through hyperedge HE-4 (induced by source paper "quantum communication query tradeoffs"):
  with members:
    - "query to communication lifting for bpp"
    - "lifting randomized query complexity to randomized communication complexity"
    - "a discrepancy lower bound for information complexity"
    - "communication complexity lower bounds by polynomials"

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)