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 "sparse combinatorial group testing for low energy massive random access"):
  Abstract: We present random access schemes for machine-type communication where a massive number of low-energy wireless devices want to occasionally transmit short information packets. We focus on the device discovery problem, with extensions to joint discovery and data transmission as well as data transmission without communicating device identities. We formulate this problem as a combinatorial group testing one, where the goal is to exactly identify the set of at most $d$ defective items from a pool of $n$ items. We translate the energy constraint at the physical layer to a constraint on the number of tests each item can participate in, and study the resulting "sparse" combinatorial group testing problem. #R##N#In our sparse setting, we restrict the number of tests each item can participate in by $w_{\max}$. It is easy to observe that if $w_{\max} \leq d$, then we must have $t=n$; i.e., testing every item individually is optimal. We show that if $w_{\max}=d+1$, the number of tests decreases suddenly from $t=n$ to $t = (d+1)\sqrt{n}$. More generally, if $w_{\max}=ld+1$ for any positive integer $l$ such that $ld+1 \leq \sqrt[l+1]{n}$, we can achieve $t=(ld+1)n^{1/(l+1)}$ using Kautz and Singleton's construction with a particular choice of field size. We also prove a nearly matching lower bound which shows that $t = \Omega(d^{2/l+1}n^{1/(l+1)})$. This shows that in the sparse setting $t$ is a fractional power of $n$, rather than logarithmic in $n$ as in the classical setting. #R##N#Since encoding and decoding efficiency can be just as important as energy efficiency, we demonstrate that our construction can be decoded in (poly$(d) + O(t)$)-time and each entry in any codeword can be computed in space poly$(\log n)$. This shows that our construction not only (nearly) achieves the fundamental lower bound, but also does that with a favorable encoding and decoding complexity.

Includes members:
  Member "on the optimality of the kautz singleton construction in probabilistic 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 "nearly optimal sparse group testing":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "group testing with runlength constraints for topological molecular storage")
  Member "low power wide area networks an overview":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "random access based reliable uplink communication and power transfer using dynamic power splitting")
  Member "capacity of the energy harvesting gaussian mac":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "capacity of a full duplex wirelessly powered communication system with self interference and processing cost")
  Member "learning immune defectives graph through group tests":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on the optimality of the kautz singleton construction in probabilistic group testing")
  Member "saffron a fast efficient and robust framework for group testing based on sparse graph codes":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on the all or nothing behavior of bernoulli group testing")
  Member "non adaptive probabilistic group testing with noisy measurements near optimal bounds with efficient algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "serial quantization for sparse time sequences")
  Member "note on noisy group testing asymptotic bounds and belief propagation reconstruction":
    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)