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 hypothesis testing against independence with multiple decision centers"):
  Abstract: A distributed binary hypothesis testing problem is studied with one observer and two decision centers. The type-II error exponents region is derived for testing against independence when the observer communicates with the two decision centers over one common and two individual noise-free bit pipes. When there is only a common noise-free bit pipe, the type-II error exponents region is derived for testing against conditional independence. Finally, when the observer can communicate to the two decision centers over a discrete memoryless broadcast channel, an achievable type-II error exponents region is derived for testing against conditional independence. The last type-II error exponent is obtained by splitting the observations into subblocks, having the transmitter apply hybrid joint source-channel coding with side-information independently to each subblock, and having each receiver apply a Neyman-Pearson test jointly over the subblocks. This decision approach avoids introducing further error exponents due to the binning or the decoding procedures.

Includes members:
  Member "hypothesis testing under maximal leakage privacy constraints":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a practical approach to navigating the tradeoff between privacy and precise utility")
  Member "distributed hypothesis testing over noisy channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "privacy aware distributed hypothesis testing")
  Member "collaborative distributed hypothesis testing":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "distributed hypothesis testing cooperation and concurrent detection")
  Member "improved source coding exponents via witsenhausen s rate":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "statistical physics of random binning")
  Member "on the capacity of the discrete memoryless broadcast channel with feedback":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "exploiting location information to enhance throughput in downlink v2i systems")

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)