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 "on the all or nothing behavior of bernoulli group testing"):
  Abstract: In this paper, we study the problem of group testing, in which one seeks to identify which items are defective given a set of suitably-designed tests whose outcomes indicate whether or not at least one defective item was included in the test. The most widespread recovery criterion seeks to exactly recovery the entire defective set, and relaxed criteria such as approximate recovery and list decoding have also been considered. In this paper, we study the fundamental limits of group testing under two significantly relaxed criteria: The {\em weak detection} criterion only seeks to distinguish (with high probability) between whether the outcomes were produced according to the group testing model or independently from the test design, and the {\em weak recovery} criterion only seeks to identify a small fraction (e.g., $0.01$) of the defective items. In the case of Bernoulli random testing, we identify scenarios in which an {\em all-or-nothing} phenomenon occurs: When the number of tests is slightly below a threshold, weak detection and weak recovery are impossible, whereas when the number of tests is slightly above the same threshold, high-probability exact recovery is possible. Our impossibility results significantly strengthen existing ones that only hold for stricter recovery criteria.

Includes members:
  Member "optimal non adaptive group testing":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "sublinear time non adaptive group testing with o k log n tests via bit mixing coding")
  Member "group testing an information theory perspective":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "group testing with runlength constraints for topological molecular storage")
  Member "performance of group testing algorithms with near constant tests per item":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "group testing with runlength constraints for topological molecular storage")
  Member "information theoretic and algorithmic thresholds for group testing":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "serial quantization for sparse time sequences")
  Member "near optimal noisy group testing via separate decoding of items":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "group testing an information theory perspective")
  Member "the capacity of bernoulli nonadaptive group testing":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "group testing with runlength constraints for topological molecular storage")
  Member "saffron a fast efficient and robust framework for group testing based on sparse graph codes":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "group testing an information theory perspective")
  Member "group testing algorithms bounds and simulations":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "serial quantization for sparse time sequences")

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)