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: "a combinatorial study of linear deterministic relay networks"
  Abstract: In the last few years the so--called "linear deterministic" model of relay channels has gained popularity as a means of studying the flow of information over wireless communication networks, and this approach generalizes the model of wireline networks which is standard in network optimization. There is recent work extending the celebrated max--flow/min--cut theorem to the capacity of a unicast session over a linear deterministic relay network which is modeled by a layered directed graph. This result was first proved by a random coding scheme over large blocks of transmitted signals. We demonstrate the same result with a simple, deterministic, polynomial--time algorithm which takes as input a single transmitted signal instead of a long block of signals. Our capacity-achieving transmission scheme for a two--layer network requires the extension of a one--dimensional Rado--Hall transversal theorem on the independent subsets of rows of a row--partitioned matrix into a two--dimensional variation for block matrices. To generalize our approach to larger networks we use the submodularity of the capacity of a cut for our model and show that our complete transmission scheme can be obtained by solving a linear program over the intersection of two polymatroids. We prove that our transmission scheme can achieve the max-flow/min-cut capacity by applying a theorem of Edmonds about such linear programs. We use standard submodular function minimization techniques as part of our polynomial--time algorithm to construct our capacity-achieving transmission scheme.

Connected through hyperedge HE-1 (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"
    - "improved combinatorial algorithms for wireless information flow"
    - "approximately achieving gaussian relay network capacity with lattice codes"
    - "combinatiorial algorithms for wireless information flow"
    - "approximate capacity of gaussian relay networks"
    - "a deterministic approach to wireless relay networks"

Connected through hyperedge HE-2 (induced by source paper "a deterministic polynomial time algorithm for constructing a multicast coding scheme for linear deterministic relay networks"):
  with members:
    - "wireless network information flow a deterministic approach"
    - "algebraic network coding approach to deterministic wireless relay networks"
    - "approximate capacity of gaussian relay networks"

Connected through hyperedge HE-3 (induced by source paper "approximately optimal wireless broadcasting"):
  with members:
    - "wireless network information flow a deterministic approach"
    - "a digital interface for gaussian relay and interference networks lifting codes from the discrete superposition model"
    - "algebraic network coding approach to deterministic wireless relay networks"
    - "noisy network coding"
    - "linear finite field deterministic networks with many sources and one destination"
    - "reciprocity in linear deterministic networks under linear coding"
    - "on approximating gaussian relay networks by deterministic networks"
    - "cooperative relay broadcast channels"

Connected through hyperedge HE-4 (induced by source paper "improved combinatorial algorithms for wireless information flow"):
  with members:
    - "combinatiorial algorithms for wireless information flow"
    - "a deterministic approach to wireless relay networks"
    - "wireless network information flow"

Connected through hyperedge HE-5 (induced by source paper "the capacity of a class of linear deterministic networks"):
  with members:
    - "transmission techniques for relay interference networks"
    - "a deterministic approach to wireless relay networks"

Connected through hyperedge HE-6 (induced by source paper "combinatiorial algorithms for wireless information flow"):
  with members:
    - "algebraic network coding approach to deterministic wireless relay networks"
    - "fast algorithm for finding unicast capacity of linear deterministic wireless relay networks"
    - "approximate capacity of gaussian relay networks"
    - "a deterministic approach to wireless relay networks"
    - "wireless network information flow"

Connected through hyperedge HE-7 (induced by source paper "fast algorithm for finding unicast capacity of linear deterministic wireless relay networks"):
  with members:
    - "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)