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: "strong converse exponent for state dependent channels with full state information at the sender and partial state information at the receiver"
  Abstract: We consider the state dependent channels with full state information with at the sender and partial state information at the receiver. For this state dependent channel, the channel capacity under rate constraint on the state information at the decoder was determined by Steinberg. In this paper, we study the correct probability of decoding at rates above the capacity. We prove that when the transmission rate is above the capacity this probability goes to zero exponentially and derive an explicit lower bound of this exponent function.

Connected through hyperedge HE-1 (induced by source paper "partial strong converse for the non degraded wiretap channel"):
  with members:
    - "new strong converse for asymmetric broadcast channels"
    - "exponent function for source coding with side information at the decoder at rates below the rate distortion function"
    - "asymptotic estimates in information theory with non vanishing error probabilities"
    - "strong converse exponent for degraded broadcast channels at rates outside the capacity region"
    - "equal image size source partitioning creating strong fano s inequalities for multi terminal discrete memoryless channels"
    - "strong converse theorems for degraded broadcast channels with feedback"
    - "converses for secret key agreement and secure computing"
    - "information spectrum approach to strong converse theorems for degraded wiretap channels"

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)