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: "collaborative distributed hypothesis testing"
  Abstract: A collaborative distributed binary decision problem is considered. Two statisticians are required to declare the correct probability measure of two jointly distributed memoryless process, denoted by Xn=(X1,…,Xn) and Yn=(Y1,…,Yn), out of two possible probability measures on finite alphabets, namely PXY and PX¯Y¯. The marginal samples given by Xn and Yn are assumed to be available at different locations. The statisticians are allowed to exchange limited amount of data over multiple rounds of interactions, which differs from previous work that deals mainly with unidirectional communication. A single round of interaction is considered before the result is generalized to any finite number of communication rounds. A feasibility result is shown, guaranteeing the feasibility of an error exponent for general hypotheses, through information-theoretic methods. The special case of testing against independence is revisited as being an instance of this result for which also an unfeasibility result is proven. A second special case is studied where zero-rate communication is imposed (data exchanges grow sub-exponentially with n) for which it is shown that interaction does not improve asymptotic performance.

Connected through hyperedge HE-1 (induced by source paper "distributed hypothesis testing cooperation and concurrent detection"):
  with members:
    - "optimal rate exponent region for a class of hypothesis testing against conditional independence problems"
    - "vector gaussian ceo problem under logarithmic loss and applications"
    - "distributed hypothesis testing with collaborative detection"
    - "distributed hypothesis testing with privacy constraints"
    - "distributed hypothesis testing with concurrent detections"
    - "on hypothesis testing against independence with multiple decision centers"
    - "hypothesis testing under mutual information privacy constraints in the high privacy regime"
    - "hypothesis testing under maximal leakage privacy constraints"

Connected through hyperedge HE-2 (induced by source paper "on the reliability function of distributed hypothesis testing under optimal detection"):
  with members:
    - "on hypothesis testing against independence with multiple decision centers"
    - "on binary distributed hypothesis testing"
    - "distributed hypothesis testing over noisy channels"
    - "hypothesis testing over the two hop relay network"
    - "a large deviations approach to secure lossy compression"
    - "distributed binary detection with lossy data compression"
    - "neyman pearson test for zero rate multiterminal hypothesis testing"
    - "on the reliability function of variable rate slepian wolf coding"

Connected through hyperedge HE-3 (induced by source paper "distributed hypothesis testing over discrete memoryless channels"):
  with members:
    - "on the reliability function of distributed hypothesis testing under optimal detection"
    - "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"
    - "unequal error protection an information theoretic perspective"

Connected through hyperedge HE-4 (induced by source paper "distributed hypothesis testing with concurrent detections"):
  with members:
    - "hypothesis testing under maximal leakage privacy constraints"
    - "rate distortion with side information at many decoders"

Connected through hyperedge HE-5 (induced by source paper "distributed hypothesis testing based on unequal error protection codes"):
  with members:
    - "distributed hypothesis testing with concurrent detections"
    - "on hypothesis testing against independence with multiple decision centers"

Connected through hyperedge HE-6 (induced by source paper "distributed hypothesis testing with collaborative detection"):
  with members:
    - "distributed hypothesis testing with concurrent detections"

Connected through hyperedge HE-7 (induced by source paper "on hypothesis testing against independence with multiple decision centers"):
  with members:
    - "hypothesis testing under maximal leakage privacy constraints"
    - "distributed hypothesis testing over noisy channels"
    - "improved source coding exponents via witsenhausen s rate"
    - "on the capacity of the discrete memoryless broadcast channel with feedback"

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)