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 "coded trace reconstruction"):
  Abstract: Motivated by average-case trace reconstruction and coding for portable DNA-based storage systems, we initiate the study of \emph{coded trace reconstruction}, the design and analysis of high-rate efficiently encodable codes that can be efficiently decoded with high probability from few reads (also called \emph{traces}) corrupted by edit errors. Codes used in current portable DNA-based storage systems with nanopore sequencers are largely based on heuristics, and have no provable robustness or performance guarantees even for an error model with i.i.d.\ deletions and constant deletion probability. Our work is a first step towards the design of efficient codes with provable guarantees for such systems. We consider a constant rate of i.i.d.\ deletions, and perform an analysis of marker-based code-constructions. This gives rise to codes with redundancy $O(n/\log n)$ (resp.\ $O(n/\log\log n)$) that can be efficiently reconstructed from $\exp(O(\log^{2/3}n))$ (resp.\ $\exp(O(\log\log n)^{2/3})$) traces, where $n$ is the message length. Then, we give a construction of a code with $O(\log n)$ bits of redundancy that can be efficiently reconstructed from $\textrm{poly}(n)$ traces if the deletion probability is small enough. Finally, we show how to combine both approaches, giving rise to an efficient code with $O(n/\log n)$ bits of redundancy which can be reconstructed from $\textrm{poly}(\log n)$ traces for a small constant deletion probability.

Includes members:
  Member "capacity results for the noisy shuffling channel":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "dna based storage models and fundamental limits")
  Member "anchor based correction of substitutions in indexed sets":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "capacity results for the noisy shuffling channel")
  Member "clustering correcting codes":
    also connected through other hyperedges:
      (none)
  Member "coding for deletion channels with multiple traces":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the error probability of maximum likelihood decoding over two deletion channels")
  Member "reconstructing trees from traces":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "trace reconstruction generalized and parameterized")
  Member "beyond trace reconstruction population recovery from the deletion channel":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "coded trace reconstruction in a constant number of traces")
  Member "trace reconstruction generalized and parameterized":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "coded trace reconstruction in a constant number of traces")
  Member "sequence subset distance and coding for error control in dna based data storage":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "capacity results for the noisy shuffling channel")

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)