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 "greedy merge degrading has optimal power law"):
  Abstract: Consider a channel with a given input distribution. Our aim is to degrade it to a channel with at most L output letters. One such degradation method is the so called "greedy-merge" algorithm. We derive an upper bound on the reduction in mutual information between input and output. For fixed input alphabet size and variable L, the upper bound is within a constant factor of an algorithm-independent lower bound. Thus, we establish that greedy-merge is optimal in the power-law sense.

Includes members:
  Member "information distilling quantizers":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "information theoretical clustering is hard to approximate")
  Member "construction of polar codes for arbitrary discrete memoryless channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "polar codes and their quantum domain counterparts")
  Member "on the construction of polar codes for channels with moderate input alphabet sizes":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "universal polarization for processes with memory")
  Member "channel upgradation for non binary input alphabets and macs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "universal polarization for processes with memory")
  Member "on the construction of polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "polar codes and their quantum domain counterparts")
  Member "at low snr asymmetric quantizers are better":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "capacity bounds for communication systems with quantization and spectral constraints")
  Member "how to construct polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "polar codes and their quantum domain counterparts")
  Member "achieving the secrecy capacity of wiretap channels using polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "explicit codes for the wiretap channel a unified design framework")

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)