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 "the error probability of maximum likelihood decoding over two deletion channels"):
  Abstract: This paper studies the problem of reconstructing a word given several of its noisy copies. This setup is motivated by several applications, among them is reconstructing strands in DNA-based storage systems. Under this paradigm, a word is transmitted over some fixed number of identical independent channels and the goal of the decoder is to output the transmitted word or some close approximation. The main focus of this paper is the case of two deletion channels and studying the error probability of the maximum-likelihood (ML) decoder under this setup. First, it is discussed how the ML decoder operates. Then, we observe that the dominant error patterns are deletions in the same run or errors resulting from alternating sequences. Based on these observations, it is derived that the error probability of the ML decoder is roughly $\frac{3q-1}{q-1}p^2$, when the transmitted word is any $q$-ary sequence and $p$ is the channel's deletion probability. We also study the cases when the transmitted word belongs to the Varshamov Tenengolts (VT) code or the shifted VT code. Lastly, the insertion channel is studied as well. These theoretical results are verified by corresponding simulations.

Includes members:
  Member "coding for sequence reconstruction for single edits":
    also connected through other hyperedges:
      (none)
  Member "tutorial on algebraic deletion correction codes":
    also connected through other hyperedges:
      (none)
  Member "coding for deletion channels with multiple traces":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "an overview of capacity results for synchronization channels")
  Member "from clustering supersequences to entropy minimizing subsequences for single and double deletions":
    also connected through other hyperedges:
      (none)
  Member "average case reconstruction for the deletion channel subpolynomially many traces suffice":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "coded trace reconstruction")
  Member "coding for racetrack memories":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "uncertainty of reconstruction with list decoding from uniform tandem duplication noise")
  Member "codes correcting a burst of deletions or insertions":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "optimal codes correcting a burst of deletions of variable length")
  Member "fundamental bounds and approaches to sequence reconstruction from nanopore sequencers":
    also connected through other hyperedges:
      (none)

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)