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 "completion delay minimization for instantly decodable network codes"):
  Abstract: In this paper, we consider the problem of minimizing the completion delay for instantly decodable network coding (IDNC), in wireless multicast and broadcast scenarios. We are interested in this class of network coding due to its numerous benefits, such as low decoding delay, low coding and decoding complexities and simple receiver requirements. We first extend the IDNC graph, which represents all feasible IDNC coding opportunities, to efficiently operate in both multicast and broadcast scenarios. We then formulate the minimum completion delay problem for IDNC as a stochastic shortest path (SSP) problem. Although finding the optimal policy using SSP is intractable, we use this formulation to draw the theoretical guidelines for the policies that can efficiently reduce the completion delay in IDNC. Based on these guidelines, we design a maximum weight clique selection algorithm, which can efficiently reduce the IDNC completion delay in polynomial time. We also design a quadratic time heuristic clique selection algorithm, which can operate in real-time applications. Simulation results show that our proposed algorithms efficiently reduce the IDNC completion delay compared to the random and maximum-rate algorithms, and almost achieve the global optimal completion delay performance over all network codes in broadcast scenarios.

Includes members:
  Member "on the complexity of solving markov decision problems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "safe imitation learning via fast bayesian reward inference from preferences")
  Member "multiuser broadcast erasure channel with feedback capacity and algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "benefits of coding on age of information in broadcast networks")
  Member "coding opportunity densification strategies for instantly decodable network coding":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "performance characterization and transmission schemes for instantly decodable network coding in wireless broadcast")
  Member "capacity of 1 to k broadcast packet erasure channels with channel output feedback":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "benefits of coding on age of information in broadcast networks")
  Member "broadcasting in time division duplexing a random linear network coding approach":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "packet loss recovery in broadcast for real time applications in dense wireless networks")
  Member "effective delay control in online network coding":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "reliability of multicast under random linear network coding")
  Member "feedback based online network coding":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "on the probability of partial decoding in sparse network coding")
  Member "informed network coding for minimum decoding delay":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "packet loss recovery in broadcast for real time applications in dense wireless networks")

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.NI(Networking and Internet Architecture)