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 "quantitative group testing in the sublinear regime"):
  Abstract: The quantitative group testing (QGT) problem deals with efficiently identifying a small number of infected individuals among a large population. To this end, we can test groups of individuals where each test returns the total number of infected individuals in the tested pool. In line with literature on related inference problems, we consider the regime where the number of infected individuals is sublinear in the total population size. We derive a sharp information-theoretic threshold for the minimum number of tests required to identify the infected individuals with high probability. Such a threshold was so far only known for the case where the infected individuals are a constant fraction of the population (Alaoui et al. 2014, Scarlett & Cevher 2017). Moreover, we propose and analyze an efficient greedy reconstruction algorithm that outperforms the best known sublinear algorithm (Karimi et al. 2019) for certain sparsity regimes.

Includes members:
  Member "sparse graph codes for non adaptive quantitative group testing":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "non adaptive quantitative group testing using irregular sparse graph codes")
  Member "performance of group testing algorithms with near constant tests per item":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on the all or nothing behavior of bernoulli group testing")
  Member "information theoretic and algorithmic thresholds for group testing":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "serial quantization for sparse time sequences")
  Member "information theoretic thresholds from the cavity method":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "optimal errors and phase transitions in high dimensional generalized linear models")
  Member "the capacity of bernoulli nonadaptive group testing":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on the all or nothing behavior of bernoulli group testing")
  Member "decoding from pooled data phase transitions of message passing":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "group testing with runlength constraints for topological molecular storage")
  Member "on the optimality of some group testing algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "group testing an information theory perspective")
  Member "improved group testing rates with constant column weight designs":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "performance of group testing algorithms with near constant tests per item")

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.DM(Discrete Mathematics)