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 "optimal rate code constructions for computationally simple channels"):
  Abstract: We consider coding schemes for computationally bounded channels, which can introduce an arbitrary set of errors as long as (a) the fraction of errors is bounded with high probability by a parameter $p$ and (b) the process which adds the errors can be described by a sufficiently simple circuit. Codes for such channel models are attractive since, like codes for standard adversarial errors, they can handle channels whose true behavior is unknown or varying over time. #R##N#For two classes of channels, we provide explicit, efficiently encodable/decodable codes of optimal rate where only inefficiently decodable codes were previously known. In each case, we provide one encoder/decoder that works for every channel in the class. The encoders are randomized, and probabilities are taken over the (local, unknown to the decoder) coins of the encoder and those of the channel. #R##N#(1) Unique decoding for additive errors: We give the first construction of a polynomial-time encodable/decodable code for additive (a.k.a. oblivious) channels that achieve the Shannon capacity $1-H(p)$. These channels add an arbitrary error vector $e\in\{0,1\}^N$ of weight at most $pN$ to the transmitted word; the vector $e$ can depend on the code but not on the particular transmitted word. #R##N#(2) List-decoding for polynomial-time channels: For every constant $c>0$, we give a Monte Carlo construction of an code with optimal rate (arbitrarily close to $1-H(p)$) that efficiently recovers a short list containing the correct message with high probability for channels describable by circuits of size at most $N^c$. We justify the relaxation to list-decoding by showing that even with bounded channels, uniquely decodable codes cannot have positive rate for $p>1/4$.

Includes members:
  Member "a characterization of the capacity of online causal binary channels":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "list decoding for oblivious arbitrarily varying macs constrained and gaussian")
  Member "beating the gilbert varshamov bound for online channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "sufficiently myopic adversaries are blind")
  Member "channel polarization a method for constructing capacity achieving codes for symmetric binary input memoryless channels":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "reed muller codes theory and algorithms")
  Member "binary causal adversary channels":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "sufficiently myopic adversaries are blind")
  Member "codes against online adversaries":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "sufficiently myopic adversaries are blind")

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)