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 "a hybrid control scheme for adaptive live streaming"):
  Abstract: The live streaming is more challenging than on-demand streaming, because the low latency is also a strong requirement in addition to the trade-off between video quality and jitters in playback. To balance several inherently conflicting performance metrics and improve the overall quality of experience (QoE), many adaptation schemes have been proposed. Bitrate adaptation is one of the major solutions for video streaming under time-varying network conditions, which works even better combining with some latency control methods, such as adaptive playback rate control and frame dropping. However, it still remains a challenging problem to design an algorithm to combine these adaptation schemes together. To tackle this problem, we propose a hybrid control scheme for adaptive live streaming, namely HYSA, based on heuristic playback rate control, latency-constrained bitrate control and QoE-oriented adaptive frame dropping. The proposed scheme utilizes Kaufman's Adaptive Moving Average (KAMA) to predict segment bitrates for better rate decisions. Extensive simulations demonstrate that HYSA outperforms most of the existing adaptation schemes on overall QoE.

Includes members:
  Member "bola near optimal bitrate adaptation for online videos":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "understanding video streaming algorithms in the wild")
  Member "qoe based low delay live streaming using throughput predictions":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "reinforcement learning based vehicle cell association algorithm for highly mobile millimeter wave communication")

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.MM(Multimedia)