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 "learn2mac online learning multiple access for urllc applications"):
  Abstract: This paper addresses a fundamental limitation of previous random access protocols, their lack of latency performance guarantees. We consider $K$ IoT transmitters competing for uplink resources and we design a fully distributed protocol for deciding how they access the medium. Specifically, each transmitter restricts decisions to a locally-generated dictionary of transmission patterns. At the beginning of a frame, pattern $i$ is chosen with probability $p^i$, and an online exponentiated gradient algorithm is used to adjust this probability distribution. The performance of the proposed scheme is showcased in simulations, where it is compared with a baseline random access protocol. Simulation results show that (a) the proposed scheme achieves good latent throughput performance and low energy consumption, while (b) it outperforms by a big margin random transmissions.

Includes members:
  Member "complexity of urllc scheduling and efficient approximation schemes":
    also connected through other hyperedges:
      (none)
  Member "online convex optimization and no regret learning algorithms guarantees and applications":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "cache optimization models and algorithms")
  Member "irregular repetition slotted aloha over the rayleigh block fading channel with capture":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "random noma with cross slot successive interference cancellation packet recovery")
  Member "q csma queue length based csma ca algorithms for achieving maximum throughput and low delay in wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on the power of randomization for scheduling real time traffic in 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)