human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "construction of polar codes with sublinear complexity"):
  Abstract: Consider the problem of constructing a polar code of block length $N$ for the transmission over a given channel $W$. Typically this requires to compute the reliability of all the $N$ synthetic channels and then to include those that are sufficiently reliable. However, we know from [1], [2] that there is a partial order among the synthetic channels. Hence, it is natural to ask whether we can exploit it to reduce the computational burden of the construction problem. #R##N#We show that, if we take advantage of the partial order [1], [2], we can construct a polar code by computing the reliability of roughly a fraction $1/\log^{3/2} N$ of the synthetic channels. In particular, we prove that $N/\log^{3/2} N$ is a lower bound on the number of synthetic channels to be considered and such a bound is tight up to a multiplicative factor $\log\log N$. This set of roughly $N/\log^{3/2} N$ synthetic channels is universal, in the sense that it allows one to construct polar codes for any $W$, and it can be computed by solving a maximum matching problem on a bipartite graph. #R##N#Our proof technique consists of reducing the construction problem to the problem of computing the maximum cardinality of a chain and of an antichain for a suitable partially ordered set. As such, this method is general and it can be used to further improve the complexity of the construction problem in case a new partial order on the synthetic channels of polar codes is discovered.

Includes members:
  Member "strange attractor for efficient polar code design":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the construction of g_n coset codes for parallel decoding")
  Member "near optimal finite length scaling for polar codes over large alphabets":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "polar codes simplicity random codes durability")
  Member "algebraic properties of polar codes from a new polynomial formalism":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "polar decreasing monomial cartesian codes")
  Member "unified scaling of polar codes error exponent scaling exponent moderate deviations and error floors":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on the polarizing behavior and scaling exponent of polar codes with product kernels")
  Member "finite length scaling for polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "reed muller codes theory and algorithms")
  Member "an entropy sumset inequality and polynomially fast convergence to shannon capacity over all alphabets":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "countably infinite multilevel source polarization for non stationary erasure distributions")
  Member "polar codes speed of polarization and polynomial gap to capacity":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "polar codes simplicity random codes durability")
  Member "improved bounds on the finite length scaling of polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "polar codes simplicity random codes durability")

Question: Please tell me which class the source paper 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)