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 "strong coordination over noisy channels with strictly causal encoding"):
  Abstract: We consider a network of two nodes separated by a noisy channel, in which the input and output signals have to be coordinated with the source and its reconstruction. In the case of strictly causal encoding and non-causal decoding, we prove inner and outer bounds for the strong coordination region and show that the inner bound is achievable with polar codes.

Includes members:
  Member "strong coordination of signals and actions over noisy channels with two sided state information":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "strategic communication with side information at the decoder")
  Member "polar codes for empirical coordination over noisy channels with strictly causal encoding":
    also connected through other hyperedges:
      (none)
  Member "strong coordination of signals and actions over noisy channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "empirical coordination subject to a fidelity criterion")
  Member "polar coding for the broadcast channel with confidential messages a random binning analogy":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "explicit codes for the wiretap channel a unified design framework")
  Member "polar coding for secret key generation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "explicit codes for the wiretap channel a unified design framework")
  Member "simulation of a channel with another channel":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "communication for generating correlation a unifying survey")
  Member "distributed channel synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "gaussian approximation of quantization error for estimation from compressed data")
  Member "achievability proof via output statistics of random binning":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "biometric and physical identifiers with correlated noise for controllable private authentication")

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)