human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "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.

Includes members:
  Member "on hypothesis testing against independence with multiple decision centers":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "distributed hypothesis testing cooperation and concurrent detection")
  Member "on binary distributed hypothesis testing":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "privacy aware distributed hypothesis testing")
  Member "distributed hypothesis testing over noisy channels":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "privacy aware distributed hypothesis testing")
  Member "hypothesis testing over the two hop relay network":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "distributed hypothesis testing over discrete memoryless channels")
  Member "a large deviations approach to secure lossy compression":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "importance of small probability events in big data information measures applications and challenges")
  Member "distributed binary detection with lossy data compression":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "privacy aware distributed hypothesis testing")
  Member "neyman pearson test for zero rate multiterminal hypothesis testing":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "distributed hypothesis testing cooperation and concurrent detection")
  Member "collaborative distributed hypothesis testing":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "distributed hypothesis testing cooperation and concurrent detection")

Question: Please tell me which class the source paper 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)