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: "two way communication with adaptive data acquisition"
  Abstract: Motivated by computer networks and machine-to-machine communication applications, a bidirectional link is studied in which two nodes, Node 1 and Node 2, communicate to fulfill generally conflicting informational requirements. Node 2 is able to acquire information from the environment, e.g., via access to a remote data base or via sensing. Information acquisition is expensive in terms of system resources, e.g., time, bandwidth and energy and thus should be done efficiently by adapting the acquisition process to the needs of the application. As a result of the forward communication from Node 1 to Node 2, the latter wishes to compute some function, such as a suitable average, of the data available at Node 1 and of the data obtained from the environment. The forward link is also used by Node 1 to query Node 2 with the aim of retrieving suitable information from the environment on the backward link. The problem is formulated in the context of multi-terminal rate-distortion theory and the optimal trade-off between communication rates, distortions of the information produced at the two nodes and costs for information acquisition at Node 2 is derived. The issue of robustness to possible malfunctioning of the data acquisition process at Node 2 is also investigated. The results are illustrated via an example that demonstrates the different roles played by the forward communication, namely data exchange, query and control.

Connected through hyperedge HE-1 (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"
    - "source coding problems with conditionally less noisy side information"
    - "a note on multiple access channels with strictly causal state 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"

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)