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 porosity of additive noise sequences"
  Abstract: Consider a binary additive noise channel with noiseless feedback. When the noise is a stationary and ergodic process $\mathbf{Z}$, the capacity is $1-\mathbb{H}(\mathbf{Z})$ ($\mathbb{H}(\cdot)$ denoting the entropy rate). It is shown analogously that when the noise is a deterministic sequence $z^\infty$, the capacity under finite-state encoding and decoding is $1-\bar{\rho}(z^\infty)$, where $\bar{\rho}(\cdot)$ is Lempel and Ziv's finite-state compressibility. This quantity is termed the \emph{porosity} $\underline{\sigma}(\cdot)$ of an individual noise sequence. A sequence of schemes are presented that universally achieve porosity for any noise sequence. These converse and achievability results may be interpreted both as a channel-coding counterpart to Ziv and Lempel's work in universal source coding, as well as an extension to the work by Lomnitz and Feder and Shayevitz and Feder on communication across modulo-additive channels. Additionally, a slightly more practical architecture is suggested that draws a connection with finite-state predictability, as introduced by Feder, Gutman, and Merhav.

Connected through hyperedge HE-1 (induced by source paper "robust gaussian joint source channel coding with a staircase distortion noise profile"):
  with members:
    - "robust gaussian joint source channel coding under the near zero bandwidth regime"
    - "minimum energy for gaussian joint source channel coding with a square law distortion noise profile"
    - "communication over individual channels"
    - "interference channels with arbitrarily correlated sources"

Connected through hyperedge HE-2 (induced by source paper "minimum energy analysis for robust gaussian joint source channel coding with a square law profile"):
  with members:
    - "communication over individual channels"
    - "interference channels with arbitrarily correlated sources"
    - "joint source channel coding with side information using hybrid digital analog codes"

Connected through hyperedge HE-3 (induced by source paper "gaussian intersymbol interference channels with mismatch"):
  with members:
    - "on the asymptotic equivalence of circulant and toeplitz matrices"
    - "on the evaluation of the polyanskiy poor verdu converse bound for finite block length coding in awgn"
    - "random coding error exponents for the two user interference channel"
    - "universal decoding for gaussian intersymbol interference channels"
    - "erasure list exponents for slepian wolf decoding"
    - "mismatched decoding error exponents second order rates and saddlepoint approximations"
    - "a general formula for the mismatch capacity"
    - "analysis of mismatched estimation errors using gradients of partition functions"

Connected through hyperedge HE-4 (induced by source paper "universal decoding for source channel coding with side information"):
  with members:
    - "exact random coding error exponents of optimal bin index decoding"
    - "erasure list exponents for slepian wolf decoding"
    - "universal decoding for arbitrary channels relative to a given class of decoding metrics"
    - "multiuser random coding techniques for mismatched decoding"
    - "communication over individual channels a general framework"
    - "communication over individual channels"
    - "universal communication part i modulo additive channels"
    - "relations between random coding exponents and the statistical physics of random codes"

Connected through hyperedge HE-5 (induced by source paper "universal decoding for gaussian intersymbol interference channels"):
  with members:
    - "asymptotic mmse analysis under sparse representation modeling"
    - "analysis of mismatched estimation errors using gradients of partition functions"
    - "universal decoding for arbitrary channels relative to a given class of decoding metrics"
    - "communication over individual channels a general framework"
    - "universal communication part i modulo additive channels"

Connected through hyperedge HE-6 (induced by source paper "universal decoding for arbitrary channels relative to a given class of decoding metrics"):
  with members:
    - "communication over individual channels a general framework"
    - "universal communication part i modulo additive channels"

Connected through hyperedge HE-7 (induced by source paper "universal communication part ii channels with memory"):
  with members:
    - "universal communication over arbitrarily varying channels"
    - "communication over individual channels"
    - "zero rate feedback can achieve the empirical capacity"
    - "universal communication part i modulo additive channels"

Connected through hyperedge HE-8 (induced by source paper "universal communication part i modulo additive channels"):
  with members:
    - "universal communication part ii channels with memory"
    - "communication over individual channels"
    - "zero rate feedback can achieve the empirical capacity"

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)