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: "gaussian assumption the least favorable but the most useful lecture notes"
  Abstract: Gaussian assumption is the most well-known and widely used distribution in many fields such as engineering, statistics, and physics. One of the major reasons why the Gaussian distribution has become so prominent is because of the central limit theorem (CLT) and the fact that the distribution of noise in numerous engineering systems is well captured by the Gaussian distribution. Moreover, features such as analytical tractability and easy generation of other distributions from the Gaussian distribution contributed further to the popularity of Gaussian distribution. Especially, when there is no information about the distribution of observations, Gaussian assumption appears as the most conservative choice. This follows from the fact that the Gaussian distribution minimizes the Fisher information, which is the inverse of the Cramer-Rao lower bound (CRLB) (or equivalently stated, the Gaussian distribution maximizes the CRLB). Therefore, any optimization based on the CRLB under the Gaussian assumption can be considered to be min-max optimal in the sense of minimizing the largest CRLB (see [1] and the references cited therein).

Connected through hyperedge HE-1 (induced by source paper "sensitivity analysis for binary sampling systems via quantitative fisher information lower bounds"):
  with members:
    - "a pessimistic approximation for the fisher information measure"
    - "measurement driven quality assessment of nonlinear systems by exponential replacement"
    - "doa parameter estimation with 1 bit quantization bounds methods and the exponential replacement"
    - "a lower bound for the fisher information measure"
    - "a general framework for transmission with transceiver distortion and some applications"
    - "information theoretic proofs of entropy power inequalities"
    - "multiple parameter estimation with quantized channel output"

Connected through hyperedge HE-2 (induced by source paper "decorrelation of neutral vector variables theory and applications"):
  with members:
    - "nonnegative hmm for babble noise derived from speech hmm application to speech enhancement"
    - "binary independent component analysis with or mixtures"

Connected through hyperedge HE-3 (induced by source paper "fisher information bounds with applications in nonlinear learning compression and inference"):
  with members:
    - "a pessimistic approximation for the fisher information measure"
    - "measurement driven quality assessment of nonlinear systems by exponential replacement"
    - "doa parameter estimation with 1 bit quantization bounds methods and the exponential replacement"
    - "capacity analysis of one bit quantized mimo systems with transmitter channel state information"
    - "a lower bound for the fisher information measure"
    - "overdemodulation for high performance receivers with low resolution adc"

Connected through hyperedge HE-4 (induced by source paper "channel and noise models for nonlinear molecular communication systems"):
  with members:
    - "symbol interval optimization for molecular communication with drift"
    - "tabletop molecular communication text messages through chemical signals"
    - "novel modulation techniques using isomers as messenger molecules for nano communication networks via diffusion"
    - "molecular communication in fluid media the additive inverse gaussian noise channel"

Connected through hyperedge HE-5 (induced by source paper "a unifying variational perspective on some fundamental information theoretic inequalities"):
  with members:
    - "an alternative proof of an extremal inequality"
    - "an alternative proof of an extremal entropy inequality"
    - "information theoretic proofs of entropy power inequalities"
    - "a multivariate generalization of costa s entropy power inequality"
    - "an extremal inequality motivated by multiterminal information theoretic problems"

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)