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: "a note on multiple access channels with strictly causal state information"
  Abstract: We propose a new inner bound on the capacity region of a memoryless multiple-access channel that is governed by a memoryless state that is known strictly causally to the encoders. The new inner bound contains the previous bounds, and we provide an example demonstrating that the inclusion can be strict. #R##N#A variation on this example is then applied to the case where the channel is governed by two independent state sequences, where each transmitter knows one of the states strictly causally. The example proves that, as conjectured by Li et al., an inner bound that they derived for this scenario can indeed by strictly better than previous bounds.

Connected through hyperedge HE-1 (induced by source paper "multiple access channels with states causally known at transmitters"):
  with members:
    - "short message quantize forward network coding"
    - "message and state cooperation in multiple access channels"
    - "noisy network coding"
    - "lecture notes on network information theory"
    - "lattice strategies for the dirty multiple access channel"
    - "multiaccess channels with state known to some encoders and independent messages"

Connected through hyperedge HE-2 (induced by source paper "capacity region of 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"
    - "multiple access channel with states known noncausally at one encoder and only strictly causally at the other encoder"
    - "on the capacity of memoryless finite state multiple access channels with asymmetric state information at the encoders"
    - "the state dependent multiple access channel with states available at a cribbing encoder"
    - "on the optimal compressions in the compress and forward relay schemes"
    - "lecture notes on network information theory"
    - "lattice strategies for the dirty multiple access channel"
    - "multiaccess channels with state known to one encoder another case of degraded message sets"

Connected through hyperedge HE-3 (induced by source paper "on the multiple access channel with asymmetric noisy state information at the encoders"):
  with members:
    - "capacity region of finite state multiple access channel with delayed state information at the transmitters"
    - "multiple access channel with states known noncausally at one encoder and only strictly causally at the other encoder"
    - "on the capacity of memoryless finite state multiple access channels with asymmetric state information at the encoders"
    - "on optimal causal coding of partially observed markov sources in single and multi terminal settings"
    - "on the structure of real time encoders and decoders in a multi terminal communication system"
    - "multiaccess channels with state known to one encoder another case of degraded message sets"
    - "finite state channels with time invariant deterministic feedback"
    - "the capacity of channels with feedback"

Connected through hyperedge HE-4 (induced by source paper "mac with action dependent state information at one encoder"):
  with members:
    - "coding with action dependent side information and additional reconstruction requirements"
    - "multiple access channels with states causally known at transmitters"
    - "two way communication with adaptive data acquisition"
    - "source coding problems with conditionally less noisy side information"
    - "multi terminal source coding with action dependent side information"
    - "multiple access channel with states known noncausally at one encoder and only strictly causally at the other encoder"
    - "multiaccess channels with state known to some encoders and independent messages"
    - "duality between channel capacity and rate distortion with two sided state information"

Connected through hyperedge HE-5 (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"
    - "capacity region of multiple access channel with states known noncausally at one encoder and only strictly causally at the other encoder"
    - "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"

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)