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: "the price of ignorance the impact of side information on delay for lossless source coding"
  Abstract: Inspired by the context of compressing encrypted sources, this paper considers the general tradeoff between rate, end-to-end delay, and probability of error for lossless sou rce coding with side-information. The notion of end-to-end delay is made precise by considering a sequential setting in which source symbols are revealed in real time and need to be reconstructed at the decoder within a certain fixed latency requirement. Upper bounds are derived on the reliability functions with delay when side-informatio n is known only to the decoder as well as when it is also known at the encoder. When the encoder is not ignorant of the side-information (including the trivial case when there is no sideinformation), it is possible to have substantially better t radeoffs between delay and probability of error at all rates . This shows that there is a fundamental price of ignorance in terms of end-to-end delay when the encoder is not aware of the side information. This effect is not visible if o nly fixed-block-length codes are considered. In this way, side-information in source-coding plays a role analogous t o that of feedback in channel coding. While the theorems in this paper are asymptotic in terms of long delays and low probabilities of error, an example is used to show that the qualitative effects describ ed here are significant even at short and moderate delays.

Connected through hyperedge HE-1 (induced by source paper "achievable moderate deviations asymptotics for streaming compression of correlated sources"):
  with members:
    - "secure multiplex coding with dependent and non uniform multiple messages"
    - "exact moderate deviation asymptotics in streaming data transmission"
    - "asymptotic estimates in information theory with non vanishing error probabilities"
    - "streaming data transmission in the moderate deviations and central limit regimes"
    - "asymmetric evaluations of erasure and undetected error probabilities"
    - "the streaming dmt of fading channels"
    - "moderate deviations in channel coding"
    - "linear error correcting codes with anytime reliability"

Connected through hyperedge HE-2 (induced by source paper "on error exponents and moderate deviations for lossless streaming compression of correlated sources"):
  with members:
    - "secure multiplex coding with dependent and non uniform multiple messages"
    - "asymptotic estimates in information theory with non vanishing error probabilities"
    - "on the dispersions of three network information theory problems"
    - "moderate deviations in channel coding"
    - "second order slepian wolf coding theorems for non mixed and mixed sources"
    - "moderate deviations of lossy source coding for discrete and gaussian sources"

Connected through hyperedge HE-3 (induced by source paper "why block length and delay behave differently if feedback is present"):
  with members:
    - "balancing forward and feedback error correction for erasure channels with unreliable feedback"
    - "channel combining and splitting for cutoff rate improvement"

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)