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: "on the information loss in memoryless systems the multivariate case"
  Abstract: In this work we give a concise definition of information loss from a system-theoretic point of view. Based on this definition, we analyze the information loss in static input-output systems subject to a continuous-valued input. For a certain class of multiple-input, multiple-output systems the information loss is quantified. An interpretation of this loss is accompanied by upper bounds which are simple to evaluate. #R##N#Finally, a class of systems is identified for which the information loss is necessarily infinite. Quantizers and limiters are shown to belong to this class.

Connected through hyperedge HE-1 (induced by source paper "information measures for deterministic input output systems"):
  with members:
    - "relative information loss in the pca"
    - "signal enhancement as minimization of relevant information loss"
    - "information loss in static nonlinearities"
    - "optimal phase transitions in compressed sensing"
    - "a characterization of entropy in terms of information loss"
    - "some results on the information loss in dynamical systems"

Connected through hyperedge HE-2 (induced by source paper "relative information loss in the pca"):
  with members:
    - "relative information loss an introduction"
    - "signal enhancement as minimization of relevant information loss"
    - "information loss in static nonlinearities"
    - "entropy of the mixture of sources and entropy dimension"

Connected through hyperedge HE-3 (induced by source paper "signal enhancement as minimization of relevant information loss"):
  with members:
    - "relative information loss in the pca"
    - "relative information loss an introduction"
    - "information loss in static nonlinearities"

Connected through hyperedge HE-4 (induced by source paper "relative information loss an introduction"):
  with members:
    - "relative information loss in the pca"

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)