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 "polarization of the r enyi information dimension for single and multi terminal analog compression"):
  Abstract: This paper shows that the R\'enyi information dimension (RID) of an i.i.d. sequence of mixture random variables polarizes to the extremal values of 0 and 1 (fully discrete and continuous distributions) when transformed by an Hadamard matrix. This provides a natural counter-part over the reals of the entropy polarization phenomenon over finite fields. It is further shown that the polarization pattern of the RID is equivalent to the BEC polarization pattern, which admits a closed form expression. These results are used to construct universal and deterministic partial Hadamard matrices for analog to analog (A2A) compression of random i.i.d. signals. In addition, a framework for the A2A compression of multiple correlated signals is developed, providing a first counter-part of the Slepian-Wolf coding problem in the A2A setting.

Includes members:
  Member "degrees of freedom in vector interference channels":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "necessary conditions for k 2 degrees of freedom")
  Member "a structured construction of optimal measurement matrix for noiseless compressed sensing via analog polarization":
    also connected through other hyperedges:
      (none)
  Member "a new entropy power inequality for integer valued random variables":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "an entropy power inequality for discrete random variables")
  Member "adaptive sensing using deterministic partial hadamard matrices":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a structured construction of optimal measurement matrix for noiseless compressed sensing via analog polarization")
  Member "information theoretically optimal compressed sensing via spatial coupling and approximate message passing":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "capacity achieving spatially coupled sparse superposition codes with amp decoding")
  Member "achieving the secrecy capacity of wiretap channels using polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "explicit codes for the wiretap channel a unified design framework")
  Member "the effect of spatial coupling on compressive sensing":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "capacity achieving spatially coupled sparse superposition codes with amp decoding")
  Member "polar codes are optimal for lossy source coding":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "polar codes and their quantum domain counterparts")

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)