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: "on the reliability function of distributed hypothesis testing under optimal detection"
  Abstract: The distributed hypothesis-testing problem with full side-information is studied. The trade-off (reliability function) between the type 1 and type 2 error exponents under limited rate is studied in the following way. First, the problem of determining the reliability function of distributed hypothesis-testing is reduced to the problem of determining the reliability function of channel-detection codes (in analogy to a similar result which connects the reliability of distributed compression and ordinary channel codes). Second, a single-letter random-coding bound based on an hierarchical ensemble, as well as a single-letter expurgated bound, are derived for the reliability of channel-detection codes. Both bounds are derived for the optimal detection rule. We believe that the resulting bounds are ensemble-tight, and hence optimal within the class of quantization-and-binning schemes.

Connected through hyperedge HE-1 (induced by source paper "privacy aware distributed hypothesis testing"):
  with members:
    - "privacy aware smart metering progress and challenges"
    - "distributed hypothesis testing with privacy constraints"
    - "technical privacy metrics a systematic survey"
    - "distributed hypothesis testing based on unequal error protection codes"
    - "privacy against a hypothesis testing adversary"
    - "distributed hypothesis testing over discrete memoryless channels"
    - "hypothesis testing under mutual information privacy constraints in the high privacy regime"
    - "on binary distributed hypothesis testing"

Connected through hyperedge HE-2 (induced by source paper "distributed hypothesis testing with variable length coding"):
  with members:
    - "strong converse using change of measure arguments"

Connected through hyperedge HE-3 (induced by source paper "distributed hypothesis testing with a privacy constraint"):
  with members:
    - "privacy aware smart metering progress and challenges"
    - "distributed hypothesis testing with privacy constraints"
    - "technical privacy metrics a systematic survey"
    - "distributed hypothesis testing based on unequal error protection codes"
    - "privacy against a hypothesis testing adversary"
    - "hypothesis testing under mutual information privacy constraints in the high privacy regime"
    - "on binary distributed hypothesis testing"
    - "privacy utility tradeoffs under constrained data release mechanisms"

Connected through hyperedge HE-4 (induced by source paper "distributed hypothesis testing over discrete memoryless channels"):
  with members:
    - "distributed hypothesis testing over noisy channels"
    - "hypothesis testing over the two hop relay network"
    - "distributed binary detection with lossy data compression"
    - "neyman pearson test for zero rate multiterminal hypothesis testing"
    - "collaborative distributed hypothesis testing"
    - "unequal error protection an information theoretic perspective"

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)