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 "the utility cost of robust privacy guarantees"):
  Abstract: Consider a data publishing setting for a data set with public and private features. The objective of the publisher is to maximize the amount of information about the public features in a revealed data set, while keeping the information leaked about the private features bounded. The goal of this paper is to analyze the performance of privacy mechanisms that are constructed to match the distribution learned from the data set. Two distinct scenarios are considered: (i) mechanisms are designed to provide a privacy guarantee for the learned distribution; and (ii) mechanisms are designed to provide a privacy guarantee for every distribution in a given neighborhood of the learned distribution. For the first scenario, given any privacy mechanism, upper bounds on the difference between the privacy-utility guarantees for the learned and true distributions are presented. In the second scenario, upper bounds on the reduction in utility incurred by providing a uniform privacy guarantee are developed.

Includes members:
  Member "estimation efficiency under privacy constraints":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the information bottleneck problems models connections applications and information theoretic views")
  Member "an estimation theoretic view of privacy":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a practical approach to navigating the tradeoff between privacy and precise utility")
  Member "f divergence inequalities":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on implicit regularization in beta vaes")
  Member "strong data processing inequalities for input constrained additive noise channels":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on data processing and majorization inequalities for f divergences with applications")
  Member "information extraction under privacy constraints":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on the information bottleneck problems models connections applications and information theoretic views")
  Member "strong data processing inequalities and phi sobolev inequalities for discrete channels":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on data processing and majorization inequalities for f divergences with applications")
  Member "utility privacy tradeoffs in databases an information theoretic approach":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a practical approach to navigating the tradeoff between privacy and precise utility")
  Member "privacy against statistical inference":
    also connected through other hyperedges:
      - Hyperedge HE-8 (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)