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 "an estimation theoretic view of privacy"):
  Abstract: We study the central problem in data privacy: how to share data with an analyst while providing both privacy and utility guarantees to the user that owns the data. We present an estimation-theoretic analysis of the privacy-utility trade-off (PUT) in this setting. Here, an analyst is allowed to reconstruct (in a mean-squared error sense) certain functions of the data (utility), while other private functions should not be reconstructed with distortion below a certain threshold (privacy). We demonstrate how a $\chi^2$-based information measure captures the fundamental PUT, and characterize several properties of this function. In particular, we give a sharp bound for the PUT. We then propose a convex program to compute privacy-assuring mappings when the functions to be disclosed and hidden are known a priori. Finally, we evaluate the robustness of our approach to finite samples.

Includes members:
  Member "the utility cost of robust privacy guarantees":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a practical approach to navigating the tradeoff between privacy and precise utility")
  Member "generalizing bottleneck problems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "obfuscation via information density estimation")
  Member "matching anonymized and obfuscated time series to users profiles":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "privacy aware time series data sharing with deep reinforcement learning")
  Member "privacy preserving adversarial networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "learning generative adversarial representations gap under fairness and censoring constraints")
  Member "context aware generative adversarial privacy":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "local information privacy and its application to privacy preserving data aggregation")
  Member "principal inertia components and applications":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "task based quantization with application to mimo receivers")
  Member "hypothesis testing under maximal leakage privacy constraints":
    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 aware mmse estimation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "local information privacy and its application to privacy preserving data aggregation")

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)