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 generalized expression for the gradient of mutual information with the application in multiple access channels"):
  Abstract: Taking a functional approach, we derive a general expression for the gradient of the Mutual Information (MI) with respect to the system parameters in the stochastic systems. This expression covers the cases in which the system input depends on the system parameters. As an application, we consider the K-user Multiple Access Channels (MAC) with feedback and utilize the obtained results to explore the behavior of these systems in terms of the MI. Specializing the results to the additive Gaussian noise MAC, we extend the MI and Minimum Mean Square Error (MMSE) relationship, i.e., I-MMSE to the K-user Gaussian MAC with feedback. In this derivation, we show that the gradient of MI can be decomposed into three distinct parts, where the first part is the MMSE term originated from noise, and the second and third parts reflect the effects of the interference and feedback, respectively. Then, considering the capacity achieving Fourier-Modulated Estimate Correction (F-MEC) strategy of Kramer, we show how feedback compensates the destructive effects of the users' interference in the K-user symmetric Gaussian MAC.

Includes members:
  Member "sum rate capacity for symmetric gaussian multiple access channels with feedback":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "transportation proof of an inequality by anantharam jog and nair")
  Member "transmitter optimization in slow fading miso wiretap channel":
    also connected through other hyperedges:
      (none)
  Member "generalized i mmse for k user gaussian channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "piggybacking codes for network coding the high low snr regime")
  Member "pointwise relations between information and estimation in gaussian noise":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on the capacity of the peak power constrained vector gaussian channel an estimation theoretic perspective")
  Member "mutual information relative entropy and estimation in the poisson channel":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a class of lower bounds for bayesian risk with a bregman loss")
  Member "mutual information and minimum mean square error in gaussian channels":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on the information bottleneck problems models connections applications and information theoretic views")

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)