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: "improved combinatorial algorithms for wireless information flow"
  Abstract: The work of Avestimehr et al. '07 has recently proposed a deterministic model for wireless networks and characterized the unicast capacity C of such networks as the minimum rank of the adjacency matrices describing all possible source-destination cuts. Amaudruz & Fragouli first proposed a polynomial-time algorithm for finding the unicast capacity of a linear deterministic wireless network in their 2009 paper. In this work, we improve upon Amaudruz & Fragouli's work and further reduce the computational complexity of the algorithm by fully exploring the useful combinatorial features intrinsic in the problem. Our improvement applies generally with any size of finite fields associated with the channel model. Comparing with other algorithms on solving the same problem, our improved algorithm is very competitive in terms of complexity.

Connected through hyperedge HE-1 (induced by source paper "bounded contention coding for wireless networks in the high snr regime"):
  with members:
    - "wireless network information flow a deterministic approach"
    - "deterministic network model revisited an algebraic network coding approach"
    - "faster information dissemination in dynamic networks via network coding"
    - "algebraic network coding approach to deterministic wireless relay networks"
    - "collision helps algebraic collision recovery for wireless erasure networks"
    - "analyzing network coding gossip made easy"
    - "dynamic sharing of a multiple access channel"

Connected through hyperedge HE-2 (induced by source paper "efficient capacity computation and power optimization for relay networks"):
  with members:
    - "near optimal nonmyopic value of information in graphical models"
    - "wireless network information flow a deterministic approach"
    - "approximately achieving gaussian relay network capacity with lattice codes"
    - "combinatiorial algorithms for wireless information flow"
    - "a combinatorial study of linear deterministic relay networks"
    - "approximate capacity of gaussian relay networks"
    - "a deterministic approach to wireless relay networks"

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.IT(Information Theory)