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: "coding for linear operator channels over finite fields"
  Abstract: Linear operator channels (LOCs) are motivated by the communications through networks employing random linear network coding (RLNC). Following the recent information theoretic results about LOCs, we propose two coding schemes for LOCs and evaluate their performance. These schemes can be used in networks employing RLNC without constraints on the network size and the field size. Our first scheme makes use of rank-metric codes and generalizes the rank-metric approach of subspace coding proposed by Silva et al. Our second scheme applies linear coding. The second scheme can achieve higher rate than the first scheme, while the first scheme has simpler decoding algorithm than the second scheme. Our coding schemes only require the knowledge of the expectation of the rank of the transformation matrix. The second scheme can also be realized ratelessly without any priori knowledge of the channel statistics.

Connected through hyperedge HE-1 (induced by source paper "multi server coded caching"):
  with members:
    - "fundamental limits of cache aided interference management"
    - "coded caching for delay sensitive content"
    - "precoding based network alignment for three unicast sessions"
    - "decentralized coded caching attains order optimal memory rate tradeoff"
    - "fundamental limits of caching"
    - "on the feasibility of precoding based network alignment for three unicast sessions"
    - "network coding for multiple unicasts an interference alignment approach"
    - "communication over finite field matrix channels"

Connected through hyperedge HE-2 (induced by source paper "batched sparse codes"):
  with members:
    - "overhead optimized gamma network codes"
    - "effects of the generation size and overlap on throughput and complexity in randomized linear network coding"
    - "on the capacity of non coherent network coding"
    - "communication over finite field matrix channels"
    - "overlapped chunked network coding"
    - "sparse network coding with overlapping classes"
    - "compute and forward harnessing interference through structured codes"
    - "packing and covering properties of subspace codes for error control in random linear network coding"

Connected through hyperedge HE-3 (induced by source paper "on multiplicative matrix channels over finite chain rings"):
  with members:
    - "communication over finite chain ring matrix channels"
    - "an algebraic approach to physical layer network coding"
    - "on the capacity of multiplicative finite field matrix channels"
    - "universal secure network coding via rank metric codes"
    - "physical layer network coding tutorial survey and beyond"
    - "on the capacity of non coherent network coding"
    - "communication over finite field matrix channels"
    - "compute and forward harnessing interference through structured codes"

Connected through hyperedge HE-4 (induced by source paper "on the capacity of multiplicative finite field matrix channels"):
  with members:
    - "beyond the cut set bound uncertainty computations in network coding with correlated sources"
    - "beyond the cut set bound uncertainty computations in network coding with correlated sources"
    - "the capacity of random linear coding networks as subspace channels"
    - "communication over finite field matrix channels"
    - "coding for errors and erasures in random network coding"
    - "on the role of mmse estimation in approaching the information theoretic limits of linear gaussian channels shannon meets wiener"

Connected through hyperedge HE-5 (induced by source paper "an upper bound on broadcast subspace codes"):
  with members:
    - "the capacity of random linear coding networks as subspace channels"
    - "on the capacity of non coherent network coding"
    - "multishot codes for network coding using rank metric codes"
    - "communication over finite field matrix channels"
    - "towards the capacity region of multiplicative linear operator broadcast channels"
    - "multishot codes for network coding bounds and a multilevel construction"
    - "a rank metric approach to error control in random network coding"
    - "coding for errors and erasures in random network coding"

Connected through hyperedge HE-6 (induced by source paper "towards the capacity region of multiplicative linear operator broadcast channels"):
  with members:
    - "the capacity of random linear coding networks as subspace channels"
    - "on the capacity of non coherent network coding"
    - "recursive code construction for random networks"
    - "communication over finite field matrix channels"
    - "multishot codes for network coding bounds and a multilevel construction"
    - "projective space codes for the injection metric"
    - "error correcting codes in projective spaces via rank metric codes and ferrers diagrams"
    - "a rank metric approach to error control in random network coding"

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)