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 "information extraction under privacy constraints"):
  Abstract: A privacy-constrained information extraction problem is considered where for a pair of correlated discrete random variables $(X,Y)$ governed by a given joint distribution, an agent observes $Y$ and wants to convey to a potentially public user as much information about $Y$ as possible without compromising the amount of information revealed about $X$. To this end, the so-called {\em rate-privacy function} is introduced to quantify the maximal amount of information (measured in terms of mutual information) that can be extracted from $Y$ under a privacy constraint between $X$ and the extracted information, where privacy is measured using either mutual information or maximal correlation. Properties of the rate-privacy function are analyzed and information-theoretic and estimation-theoretic interpretations of it are presented for both the mutual information and maximal correlation privacy measures. It is also shown that the rate-privacy function admits a closed-form expression for a large family of joint distributions of $(X,Y)$. Finally, the rate-privacy function under the mutual information privacy measure is considered for the case where $(X,Y)$ has a joint probability density function by studying the problem where the extracted information is a uniform quantization of $Y$ corrupted by additive Gaussian noise. The asymptotic behavior of the rate-privacy function is studied as the quantization resolution grows without bound and it is observed that not all of the properties of the rate-privacy function carry over from the discrete to the continuous case.

Includes members:
  Member "on maximal correlation mutual information and data privacy":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "local information privacy and its application to privacy preserving data aggregation")
  Member "lossless secure source coding yamamoto s setting":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "privacy constrained remote source coding")
  Member "notes on information theoretic privacy":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "estimation efficiency under privacy constraints")
  Member "maximal correlation secrecy":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a practical approach to navigating the tradeoff between privacy and precise utility")
  Member "extremal mechanisms for local differential privacy":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a workload adaptive mechanism for linear queries under local differential privacy")
  Member "from the information bottleneck to the privacy funnel":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on the information bottleneck problems models connections applications and information theoretic views")
  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 "bounds on inference":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "estimation efficiency under privacy constraints")

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)