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 "hardness of consensus problems for circular strings and time series averaging"):
  Abstract: Consensus problems for strings and sequences appear in numerous application contexts, ranging from bioinformatics over data mining to speech recognition. Closing some gaps in the literature, we show that some fundamental problems in this context are NP-hard, W[1]-hard, and the known (partially brute-force) exact algorithms are essentially close to optimality assuming the Exponential Time Hypothesis. Our classified problems include the Circular Consensus String problem, whose non-circular version is trivially linear-time solvable. We introduce a much more general family of circular consensus string problems that also serves as a key for our hardness reductions, and proves to be of independent (also practical) interest on its own. In particular, our work answers the main open question concerning the computational complexity of exact mean computation in dynamic time warping spaces [Brill et al., SDM 2018].

Includes members:
  Member "on the hardness of computing an average curve":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "random projections and sampling algorithms for clustering of high dimensional polygonal curves")
  Member "nonsmooth analysis and subgradient methods for averaging in dynamic time warping spaces":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "an average compress algorithm for the sample mean problem under dynamic time warping")
  Member "exact mean computation in dynamic time warping spaces":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "an average compress algorithm for the sample mean problem under dynamic time warping")
  Member "dynamic time warping and geometric edit distance breaking the quadratic barrier":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "streaming with oracle new streaming algorithms for edit distance and lcs")
  Member "quadratic conditional lower bounds for string problems and dynamic time warping":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "streaming with oracle new streaming algorithms for edit distance and lcs")
  Member "on the closest string and substring problems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on clustering incomplete data")

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.DM(Discrete Mathematics)