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 "on the minimum energy of sending gaussian multiterminal sources over the gaussian mac"):
  Abstract: In this work, we investigate the minimum energy of transmitting correlated sources over the Gaussian multiple-access channel (MAC). Compared to other works on joint source-channel coding, we consider the general scenario where the source and channel bandwidths are not naturally matched. In particular, we proposed the use of hybrid digital-analog coding over to improve the transmission energy efficiency. Different models of correlated sources are studied. We first consider lossless transmission of binary sources over the MAC. We then treat lossy transmission of Gaussian sources over the Gaussian MAC, including CEO sources and multiterminal sources. In all cases, we show that hybrid transmission achieves the best known energy efficiency.

Includes members:
  Member "hybrid digital analog codes for source channel broadcast of gaussian sources over gaussian channels":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "joint state estimation and communication over a state dependent gaussian multiple access channel")
  Member "the achievable distortion region of bivariate gaussian source on gaussian broadcast channel":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "distortion bounds for source broadcast over degraded channel")
  Member "rate region of the quadratic gaussian two encoder source coding problem":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "integer forcing architectures for uplink cloud radio access 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.IT(Information Theory)