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: "capacity region of multiple access channel with states known noncausally at one encoder and only strictly causally at the other encoder"
  Abstract: We consider a two-user state-dependent multiaccess channel in which the states of the channel are known non-causally to one of the encoders and only strictly causally to the other encoder. Both encoders transmit a common message and, in addition, the encoder that knows the states non-causally transmits an individual message. We find explicit characterizations of the capacity region of this communication model in both discrete memoryless (DM) and memoryless Gaussian cases. In particular the capacity region analysis demonstrates the utility of the knowledge of the states only strictly causally at the encoder that sends only the common message in general. More specifically, in the DM setting we show that such a knowledge is beneficial and increases the capacity region in general. In the Gaussian setting, we show that such a knowledge does not help, and the capacity is same as if the states were completely unknown at the encoder that sends only the common message. The analysis also reveals optimal ways of exploiting the knowledge of the state only strictly causally at the encoder that sends only the common message when such a knowledge is beneficial. The encoders collaborate to convey to the decoder a lossy version of the state, in addition to transmitting the information messages through a generalized Gel'fand-Pinsker binning. Particularly important in this problem are the questions of 1) optimal ways of performing the state compression and 2) whether or not the compression indices should be decoded uniquely. We show that both compression a-la noisy network coding, i.e., with no binning and non-unique decoding, and compression using Wyner-Ziv binning with backward decoding and non-unique or unique decoding are optimal.

Connected through hyperedge HE-1 (induced by source paper "multi layer gelfand pinsker strategies for the generalized multiple access channel"):
  with members:
    - "multiple access channels with states causally known at transmitters"
    - "capacity bounds for multiuser channels with non causal channel state information at the transmitters"
    - "multiple access channel with states known noncausally at one encoder and only strictly causally at the other encoder"
    - "the state dependent multiple access channel with states available at a cribbing encoder"
    - "multiple access channels with cooperative encoders and channel state information"
    - "multiaccess channels with state known to some encoders and independent messages"

Connected through hyperedge HE-2 (induced by source paper "is non unique decoding necessary"):
  with members:
    - "hybrid coding an interface for joint source channel coding and network communication"
    - "simultaneous nonunique decoding is rate optimal"
    - "interference decoding for deterministic channels"
    - "an achievability scheme for the compound channel with state noncausally available at the encoder"
    - "on the optimal compressions in the compress and forward relay schemes"

Connected through hyperedge HE-3 (induced by source paper "wyner ziv type versus noisy network coding for a state dependent mac"):
  with members:
    - "multiple access channels with states causally known at transmitters"
    - "a note on multiple access channels with strictly causal state information"
    - "multiple access channel with states known noncausally at one encoder and only strictly causally at the other encoder"
    - "on the optimal compressions in the compress and forward relay schemes"
    - "noisy network coding"

Connected through hyperedge HE-4 (induced by source paper "multiple access channel with states known noncausally at one encoder and only strictly causally at the other encoder"):
  with members:
    - "multiple access channels with states causally known at transmitters"
    - "the state dependent multiple access channel with states available at a cribbing encoder"
    - "multiaccess channels with state known to one encoder another case of degraded message sets"

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)