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: "near optimal finite length scaling for polar codes over large alphabets"
  Abstract: For any prime power $q$, Mori and Tanaka introduced a family of $q$-ary polar codes based on $q$~by~$q$ Reed-Solomon polarization kernels. For transmission over a $q$-ary erasure channel, they also derived a closed-form recursion for the erasure probability of each effective channel. In this paper, we use that expression to analyze the finite-length scaling of these codes on the $q$-ary erasure channel with erasure probability $\epsilon\in(0,1)$. Our primary result is that, for any $\gamma>0$ and $\delta>0$, there is a $q_{0}$ such that, for all $q\geq q_{0}$, the fraction of effective channels with erasure rate at most $N^{-\gamma}$ is at least $1-\epsilon-O(N^{-1/2+\delta})$, where $N=q^{n}$ is the blocklength. Since this fraction cannot be larger than $1-\epsilon-O(N^{-1/2})$, this establishes near-optimal finite-length scaling for this family of codes. Our approach can be seen as an extension of a similar analysis for binary polar codes by Hassani, Alishahi, and Urbanke. #R##N#A similar analysis is also considered for $q$-ary polar codes with $m$ by $m$ polarizing matrices. This separates the effect of the alphabet size from the effect of the matrix size. If the polarizing matrix at each stage is drawn independently and uniformly from the set of invertible $m$ by $m$ matrices, then the linear operator associated with the Lyapunov function analysis can be written in closed form. To prove near-optimal scaling for polar codes with fixed $q$ as $m$ increases, however, two technical obstacles remain. Thus, we conclude by stating two concrete mathematical conjectures that, if proven, would imply near-optimal scaling for fixed~$q$.

Connected through hyperedge HE-1 (induced by source paper "polar codes simplicity random codes durability"):
  with members:
    - "reed muller codes polarize"
    - "ar i kan meets shannon polar codes with near optimal convergence to channel capacity"
    - "explicit polar codes with small scaling exponent"
    - "on the capacity of channels with deletions and states"
    - "polar codes for the deletion channel weak and strong polarization"
    - "polar like codes and asymptotic tradeoff among block length code rate and error probability"
    - "scaling exponent and moderate deviations asymptotics of polar codes for the awgn channel"
    - "relaxed polar codes"

Connected through hyperedge HE-2 (induced by source paper "ar i kan meets shannon polar codes with near optimal convergence to channel capacity"):
  with members:
    - "explicit polar codes with small scaling exponent"
    - "general strong polarization"
    - "binary linear codes with optimal scaling and quasi linear complexity"
    - "multi kernel polar codes proof of polarization and error exponents"
    - "multi kernel construction of polar codes"
    - "unified scaling of polar codes error exponent scaling exponent moderate deviations and error floors"
    - "finite length scaling for polar codes"
    - "polar codes speed of polarization and polynomial gap to capacity"

Connected through hyperedge HE-3 (induced by source paper "explicit polar codes with small scaling exponent"):
  with members:
    - "efficient decoding of polar codes with some 16 16 kernels"
    - "binary linear codes with optimal scaling polar codes with large kernels"
    - "binary linear codes with optimal scaling and quasi linear complexity"
    - "polar coding for non stationary channels"
    - "fast polarization and finite length scaling for non stationary channels"
    - "unified scaling of polar codes error exponent scaling exponent moderate deviations and error floors"
    - "finite length scaling for polar codes"
    - "channel polarization a method for constructing capacity achieving codes for symmetric binary input memoryless channels"

Connected through hyperedge HE-4 (induced by source paper "polar like codes and asymptotic tradeoff among block length code rate and error probability"):
  with members:
    - "performance bounds of concatenated polar coding schemes"
    - "scaling exponent and moderate deviations asymptotics of polar codes for the awgn channel"
    - "relaxed polar codes"
    - "minimum distance based construction of multi kernel polar codes"
    - "multi kernel polar codes proof of polarization and error exponents"
    - "a note on some inequalities used in channel polarization and polar coding"
    - "multi kernel construction of polar codes"
    - "flexible length polar codes through graph based augmentation"

Connected through hyperedge HE-5 (induced by source paper "general strong polarization"):
  with members:
    - "on error correction performance and implementation of polar code list decoders for 5g"
    - "binary linear codes with optimal scaling and quasi linear complexity"
    - "polar codes for broadcast channels"
    - "unified scaling of polar codes error exponent scaling exponent moderate deviations and error floors"
    - "finite length scaling for polar codes"
    - "an entropy sumset inequality and polynomially fast convergence to shannon capacity over all alphabets"
    - "polar coding for interference networks"
    - "polar codes speed of polarization and polynomial gap to capacity"

Connected through hyperedge HE-6 (induced by source paper "polar code moderate deviation recovering the scaling exponent"):
  with members:
    - "general strong polarization"
    - "finite length scaling for polar codes"
    - "polar codes speed of polarization and polynomial gap to capacity"
    - "improved bounds on the finite length scaling of polar codes"
    - "on the correlation between polarized becs"
    - "scaling exponent of list decoders with applications to polar codes"
    - "rate dependent analysis of the asymptotic behavior of channel polarization"
    - "polar codes characterization of exponent bounds and constructions"

Connected through hyperedge HE-7 (induced by source paper "algebraic matching techniques for fast decoding of polar codes with reed solomon kernel"):
  with members:
    - "list decoding of polar codes"
    - "source and channel polarization over finite fields and reed solomon matrices"
    - "polar codes characterization of exponent bounds and constructions"

Connected through hyperedge HE-8 (induced by source paper "binary linear codes with optimal scaling polar codes with large kernels"):
  with members:
    - "achieving the uniform rate region of general multiple access channels by polar coding"
    - "construction of polar codes with sublinear complexity"
    - "finite length scaling for polar codes"
    - "performance limits and practical decoding of interleaved reed solomon polar concatenated codes"
    - "polar codes speed of polarization and polynomial gap to capacity"
    - "scaling exponent of list decoders with applications to polar codes"
    - "rate dependent analysis of the asymptotic behavior of channel polarization"
    - "spatially coupled ensembles universally achieve capacity under belief propagation"

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)