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 "upper bounds on the relative entropy and r enyi divergence as a function of total variation distance for finite alphabets"):
  Abstract: A new upper bound on the relative entropy is derived as a function of the total variation distance for probability measures defined on a common finite alphabet. The bound improves a previously reported bound by Csisz\'ar and Talata. It is further extended to an upper bound on the R\'enyi divergence of an arbitrary non-negative order (including $\infty$) as a function of the total variation distance.

Includes members:
  Member "optimal quantization for distribution synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a note on reverse pinsker inequalities")
  Member "on the r e nyi divergence and the joint range of relative entropies":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "bounds among f divergences")
  Member "bounds among f divergences":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "empirical and strong coordination via soft covering with polar codes")
  Member "channels with cost constraints strong converse and dispersion":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "finite sample analysis of image registration")
  Member "renyi divergence and kullback leibler divergence":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "review analyze and design a comprehensive deep reinforcement learning framework")
  Member "a tight upper bound for the third order asymptotics for most discrete memoryless channels":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "finite sample analysis of image registration")
  Member "entropy bounds for discrete random variables via maximal coupling":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "minimum entropy couplings and their applications")
  Member "on pinsker s and vajda s type inequalities for csiszar s f divergences":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "theoretical evidence for adversarial robustness through randomization")

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)