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 "sublinear time non adaptive group testing with o k log n tests via bit mixing coding"):
  Abstract: The group testing problem consists of determining a small set of defective items from a larger set of items based on tests on groups of items, and is relevant in applications such as medical testing, communication protocols, pattern matching, and many more. While rigorous group testing algorithms have long been known with polynomial runtime, approaches permitting a decoding time {\em sublinear} in the number of items have only arisen more recently. In this paper, we introduce a new approach to sublinear-time non-adaptive group testing called {\em bit mixing coding} (BMC). We show that BMC achieves asymptotically vanishing error probability with $O(k \log n)$ tests and $O(k^2 \cdot \log k \cdot \log n)$ runtime, where $n$ is the number of items and $k$ is the number of defectives, in the limit as $n \to \infty$ (with $k$ having an arbitrary dependence on $n$). This closes a key open problem of simultaneously achieving $\mathrm{poly}(k \log n)$ decoding time using $O(k \log n)$ tests without any assumptions on $k$. In addition, we show that the same scaling laws can be attained in a commonly-considered noisy setting, in which each test outcome is flipped with constant probability.

Includes members:
  Member "optimal non adaptive group testing":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the all or nothing behavior of bernoulli group testing")
  Member "group testing an information theory perspective":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on the all or nothing behavior of bernoulli group testing")
  Member "simple codes and sparse recovery with fast decoding":
    also connected through other hyperedges:
      (none)
  Member "performance of group testing algorithms with near constant tests per item":
    also connected through other hyperedges:
      - Hyperedge HE-3 (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-4 (induced by source paper "serial quantization for sparse time sequences")
  Member "cross sender bit mixing coding":
    also connected through other hyperedges:
      (none)
  Member "on the optimality of the kautz singleton construction in probabilistic group testing":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "learning erd h o s r enyi random graphs via edge detecting queries")
  Member "near optimal noisy group testing via separate decoding of items":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on the all or nothing behavior of bernoulli group testing")

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)