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: "on the wyner ziv problem for individual sequences"
  Abstract: We consider a variation of the Wyner-Ziv problem pertaining to lossy compression of individual sequences using finite-state encoders and decoders. There are two main results in this paper. The first characterizes the relationship between the performance of the best $M$-state encoder-decoder pair to that of the best block code of size $\ell$ for every input sequence, and shows that the loss of the latter relative to the former (in terms of both rate and distortion) never exceeds the order of $(\log M)/\ell$, independently of the input sequence. Thus, in the limit of large $M$, the best rate-distortion performance of every infinite source sequence can be approached universally by a sequence of block codes (which are also implementable by finite-state machines). While this result assumes an asymptotic regime where the number of states is fixed, and only the length $n$ of the input sequence grows without bound, we then consider the case where the number of states $M=M_n$ is allowed to grow concurrently with $n$. Our second result is then about the critical growth rate of $M_n$ such that the rate-distortion performance of $M_n$-state encoder-decoder pairs can still be matched by a universal code. We show that this critical growth rate of $M_n$ is linear in $n$.

Connected through hyperedge HE-1 (induced by source paper "on the data processing theorem in the semi deterministic setting"):
  with members:
    - "perfectly secure encryption of individual sequences"

Connected through hyperedge HE-2 (induced by source paper "universal wyner ziv coding for distortion constrained general side information"):
  with members:
    - "channel coding and lossy source coding using a generator of constrained random numbers"
    - "tight exponential analysis of universally composable privacy amplification and its applications"
    - "achievability proof via output statistics of random binning"
    - "reliability in source coding with side information"
    - "rate distortion with side information at many decoders"
    - "the rate distortion function for product of two sources with side information at decoders"
    - "universal source coding over generalized complementary delivery networks"
    - "efficient on line schemes for encoding individual sequences with side information at the decoder"

Connected through hyperedge HE-3 (induced by source paper "perfectly secure encryption of individual sequences"):
  with members:
    - "universal communication part i modulo additive channels"
    - "efficient on line schemes for encoding individual sequences with side information at the decoder"
    - "on context tree prediction of individual sequences"

Connected through hyperedge HE-4 (induced by source paper "structure theorems for real time variable rate coding with and without side information"):
  with members:
    - "information theoretic viewpoints on optimal causal coding decoding problems"
    - "on real time coding with limited lookahead"

Connected through hyperedge HE-5 (induced by source paper "universal coding for lossless and lossy complementary delivery problems"):
  with members:
    - "universal source coding over generalized complementary delivery networks"
    - "multiterminal source coding with complementary delivery"
    - "universal coding for correlated sources with complementary delivery"

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)