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 almost disjunct matrices for group testing"):
  Abstract: In a group testing scheme, a set of tests is designed to identify a small number t of defective items among a large set (of size N) of items. In the non-adaptive scenario the set of tests has to be designed in one-shot. In this setting, designing a testing scheme is equivalent to the construction of a disjunct matrix, an M ×N matrix where the union of supports of any t columns does not contain the support of any other column. In principle, one wants to have such a matrix with minimum possible number M of rows (tests). One of the main ways of constructing disjunct matrices relies on constant weight error-correcting codes and their minimum distance. In this paper, we consider a relaxed definition of a disjunct matrix known as almost disjunct matrix. This concept is also studied under the name of weakly separated design in the literature. The relaxed definition allows one to come up with group testing schemes where a close-to-one fraction of all possible sets of defective items are identifiable. Our main contribution is twofold. First, we go beyond the minimum distance analysis and connect the average distance of a constant weight code to the parameters of an almost disjunct matrix constructed from it. Next we show as a consequence an explicit construction of almost disjunct matrices based on our average distance analysis. The parameters of our construction can be varied to cover a large range of relations for t and N. As an example of parameters, consider any absolute constant e > 0 and t proportional to N δ , δ > 0. With our method it is possible to explicitly construct a group testing scheme that identifies (1 − e) proportion of all possible defective sets of size t using only \(O\Big(t^{3/2}\sqrt{ \log(N/\epsilon)}\Big)\) tests (as opposed to O(t 2logN) required to identify all defective sets).

Includes members:
  Member "improved constructions for non adaptive threshold group testing":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "improved non adaptive algorithms for threshold group testing with a gap")
  Member "construction of a large class of deterministic sensing matrices that satisfy a statistical isometry property":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "frame moments and welch bound with erasures")
  Member "explicit non adaptive combinatorial group testing schemes":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "group testing with runlength constraints for topological molecular storage")

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)