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: "asymptotics of input constrained erasure channel capacity"
  Abstract: In this paper, we examine an input-constrained erasure channel and we characterize the asymptotics of its capacity when the erasure rate is low. More specifically, for a general memoryless erasure channel with its input supported on an irreducible finite-type constraint, we derive partial asymptotics of its capacity, using some series expansion type formulas of its mutual information rate; and for a binary erasure channel with its first-order Markovian input supported on the $(1, \infty)$-RLL constraint, based on the concavity of its mutual information rate with respect to some parameterization of the input, we numerically evaluate its first-order Markov capacity and further derive its full asymptotics. The asymptotics obtained in this paper, when compared with the recently derived feedback capacity for a binary erasure channel with the same input constraint, enable us to draw the conclusion that feedback may increase the capacity of an input-constrained channel, even if the channel is memoryless.

Connected through hyperedge HE-1 (induced by source paper "computable lower bounds for capacities of input driven finite state channels"):
  with members:
    - "feedback capacity and coding for the bibo channel with a no repeated ones input constraint"
    - "dual capacity upper bounds for noisy runlength constrained channels"
    - "novel lower bounds on the entropy rate of binary hidden markov processes"
    - "a single letter upper bound on the feedback capacity of unifilar finite state channels"

Connected through hyperedge HE-2 (induced by source paper "feedback capacity and coding for the bibo channel with a no repeated ones input constraint"):
  with members:
    - "dual capacity upper bounds for noisy runlength constrained channels"
    - "a single letter upper bound on the feedback capacity of unifilar finite state channels"
    - "an efficient feedback coding scheme with low error probability for discrete memoryless channels"
    - "a simple proof for the optimality of randomized posterior matching"
    - "can feedback increase the capacity of the energy harvesting channel"
    - "extrinsic jensen shannon divergence applications to variable length coding"
    - "capacity and coding for the ising channel with feedback"
    - "optimal feedback communication via posterior matching"

Connected through hyperedge HE-3 (induced by source paper "capacity of burst noise erasure channels with and without feedback and input cost"):
  with members:
    - "feedback capacity and coding for the bibo channel with a no repeated ones input constraint"
    - "feedback does not increase the capacity of compound channels with additive noise"
    - "can feedback increase the capacity of the energy harvesting channel"
    - "zero delay sequential transmission of markov sources over burst erasure channels"
    - "windowed decoding of protograph based ldpc convolutional codes over erasure channels"
    - "capacity and coding for the ising channel with feedback"
    - "a coding theorem for a class of stationary channels with feedback"
    - "finite state channels with time invariant deterministic feedback"

Connected through hyperedge HE-4 (induced by source paper "capacity of remotely powered communication"):
  with members:
    - "capacity of the energy harvesting channel with a finite battery"
    - "energy harvesting wireless communications a review of recent advances"
    - "can feedback increase the capacity of the energy harvesting channel"
    - "capacity of the awgn channel with random battery recharges"
    - "universally near optimal online power control for energy harvesting nodes"
    - "subblock constrained codes for real time simultaneous energy and information transfer"
    - "near optimal energy control and approximate capacity of energy harvesting communication"
    - "constrained codes for joint energy and information transfer"

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)